On 2023-01-28 14:51:44, user Luis Matheu Wyld wrote:

Interesting .....that peptide signals looks familiar ...is it protease Target site?

On 2021-10-28 14:59:28, user Christina Lebonville wrote:

I definitely would like to see the coordinates used for the ROIs in the final version :) Really cool work!

On 2025-11-12 17:13:41, user Leslie Sanderson wrote:

The links for "View current version of this article" and "Now published in Microbial Biotechnology...." are incorrect and instead link to a different article by the same authors. This article has been published in Microbiology ( https://doi.org/10.1099/mic.0.000997 )

On 2017-07-27 14:03:31, user David Howard wrote:

We have been made aware of an issue with some of the imputation conducted by UK Biobank. We are rerunning our downstream analyses and will update the paper in due course.

On 2017-05-27 09:07:01, user Leonid Schneider wrote:

Two points:<br /> 1. If an institution is invited to separately assess scientific quality of a manipulated paper, they might be biased to find enough of that elusive quality and not request retraction. In fact, it happens all the time, like University of Bremen behaved in Kathrin Maedler case. <br /> https://forbetterscience.co...<br /> 2. Journals should avoid colluding too much with universities, otherwise rigged institutional investigations will influence editorial decision, like it happened in Maria Pia Cosma's case with Cell. <br /> https://forbetterscience.co...

On 2020-05-07 15:43:53, user Concerned Citizen wrote:

For reference, here's some prominent virologists saying this analysis overinterprets the observed data and more analysis is required to make these claims:<br /> https://twitter.com/firefox...<br /> https://twitter.com/angie_r...<br /> https://twitter.com/trvrb/s...

On 2022-01-14 18:34:17, user Peter Chuckran wrote:

Link to published article

https://academic.oup.com/fe...

On 2016-06-08 22:19:49, user John Urban wrote:

Any chance you can tell me the exact commands used for the platanus -> dbg2olc -> blasr -> pbdagcon ? <br /> I have had no luck getting dbg2olc running...

Another Q:<br /> platanus has 3 steps: assemble, scaffold, and gap close. It seems like the dbg2olc authors recommend not performing the scaffold and gap close steps:<br /> """Please make sure they are the raw DBG contigs without using repeat resolving techniques such as gap closing or scaffolding. Otherwise you may have poor final results due to the errors introduced by the heuristics used in short read assembly pipelines."""<br /> So did you use only the assemble step?

On 2019-03-13 11:53:07, user Giorgio Cattoretti wrote:

The method proposed for AF subtraction is in fact a method for object subtraction, based on thresholding and segmenting and results in loss of substantial information from the image.<br /> Fig.2 indeed shows entire macrophages removed.

Prior art, not quoted by the Authors, has a more efficient and intelligent method of subtracting the AF signal pixel by pixel, maintaining the full information even in autofluorescent objects and does not need sophisticate equipment or software.<br /> Pang, Z, et al Autofluorescence removal using a customized filter set. Microsc Res Tech. 2013;76:1007–1015. DOI: 10.1002/jemt.22261<br /> Pang, Z, et al. Dark pixel intensity determination and its applications in normalizing different exposure time and autofluorescence removal. J Microsc. 2012;246:1–10. DOI: 10.1111/j.1365-2818.2011.03581.x<br /> Van de Lest, CH, et al. Elimination of autofluorescence in immunofluorescence microscopy with digital image processing. J Histochem Cytochem. 1995;43:727–30. https://doi.org/10.1177/43....

We used extensively and published a method based on those refs:<br /> Bolognesi MM et al, JoHC 65 (8):431-444, 2017<br /> https://doi.org/10.1369/002.... (see Suppl. Fig. 2)<br /> In essence, in AF objects, the level of AF in each pixel is subtracted from the signal+AF level, leaving a 0 pixel background value and only the specific signal value. No information is lost from the image.<br /> Although the automation proposed by the Authors is quite welcome, the loss of information may not be acceptable, except for selected aesthetic purposes.<br /> Best regards

On 2019-04-14 11:24:46, user ???? wrote:

Thank you for your interests on quick freeze, deep etch EM.<br /> We believe this method is really useful for PG studies.

We have been studying about motility mechanisms of class Mollicutes.<br /> Recently, we got interests on the role of PG on survival and evolution, because class Mollicutes quit it by some reason.

We hope we can do some contributions to PG field.<br /> Any comments are welcome. <br /> Makoto MIYATA

On 2021-06-01 14:16:32, user Bas Heijmans wrote:

Nice work, Roza and Anthony et al. We recently reported on TFs affecting DNAm in Genome Biol (https://genomebiology.biome... "https://genomebiology.biomedcentral.com/articles/10.1186/s13059-020-02114-z)"). Those were very much enriched for Zinc fingers (in particular with KRAB domain). Any overlap between your and our list? Or are our studies an example of the difference you will see when looking at different tissues and different 'developmental' stages? Will be interested to read your thoughts.

On 2021-05-11 00:22:05, user Jon wrote:

Interesting study. Klaus Kaestner group has recently published a paper describing the interaction of FOXA1 with demethylation pathways in a developmental context, the authors might want to cite and discuss it https://www.sciencedirect.c...

On 2020-09-07 14:22:51, user Todd Steck wrote:

How does the VBNC state impact interpretation of your results?

On 2020-02-02 02:44:09, user Mingchiu Fung wrote:

Can a CoV and HIV undergo recombination? I doubt it.

On 2020-02-01 16:05:38, user Dzogchen wrote:

This report highlights the dangers of assuming significance to a highly improbable yet random occurrence. If one calculates the probability of finding all four peptides within the HIV-1 genome it is improbable but that does not infer non-randomness. Lots of highly improbable events happen in nature that are in fact random. Even if you constrain to just the viral sequences in the database which are nearly 6 million residues (protein) the probability is quite low that all 4 peptides match HIV-1 but the authors fell into the trap of assigning significance to randomness.

On 2025-10-20 17:55:20, user Patrick Jordan wrote:

Peer Review Materials and Methods:

Phosphoproteomics uncovers rapid and specific transition from plant two-component system signaling to Ser/Thr2phosphorylation by the intracellular redox sensor AHK531

Not necessarily relegated to materials and methods sections of the article but found throughout the abstract and introduction is a lack of background in the subject along with relevance to the continuance of research in this field and importance to biology.<br /> Typical diploid organism experimental design studying a specific genotype for expression involves using a homozygous wild-type (+/+), heterozygous mutant with one copy of the allele (+/-), and a homozygous mutant with the gene knocked out (-/-). This study only utilized Arabidopsis ahk5-1 (Col-0) as their homozygous mutant and compared the treatment with the wild-type homozygous Arabidopsis. Why was the heterozygote not included in the study? Is there any phenotypic difference between the WT and the knockout strain? Growth rates, appearance, stress tolerance, etc.? If the AHK5 gene is critical in signaling during stress, there should be a phenotype of deficient stress tolerance. The experimental design also did not involve replicants or parallel experiments during the metabolic labeling procedures<br /> Another problematic issue is the type of water used. During the treatment stage, the control “mock” treatment added an equivalent amount of water to the seedlings but does not specify the type of water (i.e. DI water vs. tap). Later, after incubation of the treatment methods, the seedlings are rinsed specifically with tap water. Components of tap water vs. DI water can have differences in mineral content and affect the protein extraction results.<br /> The protein extraction procedure was modified where instead of grinding in a mortar and pestle as per procedures established2,3, the liquid nitrogen frozen plant matter was coarsely crushed. The reasoning for this was not established. During the proteome quantification procedure, hits to contaminants were excluded. Why was this? Contaminants added during the procedures could remain undetected because of this.

References<br /> (1) Drechsler, T.; Li, Z.; Schulze, W. X.; Harter, K. Phosphoproteomics Uncovers Rapid and Specific Transition from Plant Two-Component System Signaling to Ser/Thr Phosphorylation by the Intracellular Redox Sensor AHK5. October 14, 2025. https://doi.org/10.1101/2025.10.13.682113 .<br /> (2) Dautel, R. MOLECULAR CHARACTERIZATION OF THE ARABIDOPSIS THALIANA HISTIDINE KINASE 1; 2016.<br /> (3) Wu, X. N.; Schulze, W. X. Phosphopeptide Profiling of Receptor Kinase Mutants. Methods in Molecular Biology 2015, 1306, 71–79. https://doi.org/10.1007/978-1-4939-2648-0_5 .

On 2020-10-28 18:45:57, user David Holcman wrote:

The text of this paper is available for modification and reuse under <br /> the terms of the Creative Commons Attribution-Sharealike 3.0 Unported <br /> License and the GNU Free Documentation License. In particular, it can be used for Wikipedia.<br /> D. Holcman--the lead author.

On 2019-07-25 18:08:05, user David Marjanovic wrote:

The reference to Marjanovic and Laurin (2018) in the last paragraph is a typo for 2019.

On 2020-04-20 08:34:55, user Lukasz Sobala wrote:

Can't see the scale bar in Figure 1.

On 2017-11-24 08:15:47, user Christoph Bleidorn wrote:

See published version in FEMS Microbiology Ecology: https://academic.oup.com/fe...

On 2021-07-08 10:55:42, user Jelger Risselada wrote:

After the manuscript has been accepted via the regular peer reviewed process the here-used EVOMD code will be made publicly accessible on github. Nevertheless, if you are willing to already try out or use our evoMD method simply drop us a line.

On 2017-03-28 12:20:30, user jb.anderson wrote:

The 19 sequences of strains designated "Pdxxxx" were gifted to us, but accession numbers to a public archive are not yet available. In a separate analysis, we excluded these 19, retained 18 of our strains plus five sequences of N. American strains of P. destructans from the public archive (SRR3545533, SRR3545532, SRR3545531, SRR3545530, and SRR1952982). In that analysis, we reach exactly the same conclusions in an equally robust manner. - The authors

On 2021-09-30 01:36:37, user Susaki EA/suishess wrote:

In the method section, we would appreciate it if the authors refer to our 3D histology paper (ref 14) for HEPES/Triton/NaCl/Quadrol/Urea immunostaining buffer because the recipe is not standard in histology and was explicitly developed for CUBIC-HV 3D staining.

On 2020-12-10 23:41:36, user Kathleen Lyons wrote:

This article has been published in PLOS ONE<br /> https://doi.org/10.1371/jou...

On 2018-12-27 19:29:09, user John Didion wrote:

"However, RAUR is not publicly available and hence could not be considered for Genesis-indel pipeline."

Dear authors, I have just learned of this fabulous new tool, "Google," for finding things on the internet.

http://bioinformatics.csu.e...

On 2016-12-06 16:07:04, user Pat Schloss wrote:

To be clear, I was not asked to review this manuscript by a journal and have no connection to uBiome. This review has been cross posted at http://www.academichermit.c... and makes reference to the version of the preprint posted on October 31, 2016.

Almonacid and colleagues describe the use of 16S rRNA gene sequencing as a clinical diagnostic tool for detecting the presence of bacteria and archaea commonly associated with fecal samples in health and disease. On the whole, the method is not novel in that many people have been doing 16S rRNA gene sequencing of samples for many years now. The potential novelty of the manuscript is that it attempts to place the value of this technology in a clinical diagnostics rather than exploratory setting. The potential impact of this paper is reduced because it is more of a proof of concept rather than a comparative demonstration relative to other methods. Overall, the methods are poorly described and there are a number of overly generalized claims that are not supported by the literature or their data. The most glaring problem is that the authors assume that the presence of a V4 sequence that is identical to that of a pathogen is proof for evidence of the organism.

Major comments

1. L16-18, 43-51. I'm curious whether the authors actually have citations to back up the primacy of manual culture-based methods in clinical diagnostic laboratories or their limitations. My understanding is the much of clinical diagnostics is highly automated and while it may use some amount of cultivation, the actual analyses are quite modern. The authors at least need to recognize the high levels of automation and use of qPCR, ELISA, and mass spectroscopy-based approaches in most diagnostic labs. In fact, the authors later use one of these methods, Luminex‘s xTAG Gastrointestinal Pathogen Panel to help develop the panel of organisms used in their own method. The authors' new method may be novel, but they should portray its novelty using a relative modern comparison rather than a straw man. The manuscript would be considerably strengthened by comparing the Luminex method (or any other method) to the current method.

2. The authors have tested whether they are able to distinguish distantly related pathogens, but have not done due diligence in determining whether the approach can distinguish pathogenic and non-pathogenic organisms. As an example, they state that "the pathogen Peptoclostridium difficile is found in ~2% of the healthy cohort which shows that asymptomatic P. difficile colonization is not uncommon in healthy individuals (L211)." This statement is emblematic of a number of problems with the authors' analysis. First, the presence of P.difficile/C.difficile does not mean that it is in fact pathogen as there are many non-toxigenic and, thus non-pathogenic, strains of this organism - the V4 region is simply not a virulence factor. Second, there is already a toxin-based assay for toxin-producing strains that is likely more sensitive and specific than this sequence-based approach and much cheaper for this and other pathogens. Third, the V4 region is only about 250 nt in length. There is always the risk that closely related, but different organisms may have the same sequence and that the same organism may generate different sequences because there is intra-genomic variation. When I used blastn to compare the region of the P. difficile sequence in Table S2 that would be amplified by their primers to NCBI's reference 16S rRNA gene sequences, it returned two additional P. difficile strains (JCM 1296 and ATCC 9689) that are identical to each other but 1 nt different than the sequence in Table S2. It is interesting that none of the sequences in the NCBI reference were an exact match as required by the current method. When I performed a similar analysis using the author's E. coli/Shigella sequence, it matched multiple Escherichia and Shigella strains, most of which were not pathogenic. Based on all of this, I am not sure how much utility a clinical diagnostic laboratory would gain from using this method over others. None of these points are considered in the authors' discussion.

3. The authors lay out a "healthy reference range" for each of their 28 targets (L199-210). I worry about such a claim, when really the authors are likely only defining an operational healthy range so that they can optimize the sensitivity and specificity of pathogen detection. Claiming a healthy range as they have assumes that the subjects are truly healthy (there is no indication of whether the subjects were honest in self-reporting) and that the microbial communities did not change between collection and analysis. To this second point, the Methods are poorly described and validated. Specifically, I am unclear what "specifications" were laid out by the NIH Human Microbiome Project that would be relevant for this method (L100-102). Furthermore, what is the composition of the lysis and stabilization buffer that allows samples to be stored at ambient temperatures. The authors need to either provide data or a reference to support this claim including evidence that the community composition does not change. All this is necessary to report for others hoping to repeat the authors' work and for improving the clarity of the writing.

4. I am impressed by the authors' ability to quantify the relative abundance of these strains using PCR and sequencing. This runs a bit counter to the prevailing wisdom that there are PCR biases at work that would skew the representation of taxa such that the final proportions are not representative of the initial proportions. I'm a bit confused by the description of the experiment. Namely, what was the diluent DNA that is mentioned in the Methods (L142)? Although the quantitative results are impressive, I am a bit concerned that the authors used DNA fragments that overlap the V4 region of the 16S rRNA gene rather than genomic DNA.

5. Similar to the previously described concerns regarding the methods description, the list of accessions in the curated database that is described should be made publicly available since this is a critical component to the method (L171-185). More details are needed that describe how this database was created. The manuscript states "After optimizing the confusion matrices for all preliminary targets...", but it is unclear what "optimizing" means and what was altered to generate better performance. Furthermore, I am curious whether uBiome paid for a license to use the SILVA reference. Unlike many other references, this is not a database that is free for non-academic usage (https://www.arb-silva.de/si... "https://www.arb-silva.de/silva-license-information)"). Considering they are a for-profit company and are likely to commercialize this, they may want to consider a database that is more public. That being said, I don't know why the authors would need to use the SILVA reference since they are not making use of the alignment, taxonomy, or metadata features contained within the database.

Minor comments:

1. L78-80. "Regularly evaluating the microbiome to monitor overall health is therefore gaining traction in contemporary medicine and needs to be part of modern diagnostics."

2. L102-109 include no citations. Although these may be "standard protocols", specific protocols should still be cited as there are no standards and to give credit to those that developed the protocols.

3. L112-125. The authors present a method for denoising and building contigs from their sequence data that uses Swarm. As far as I know, this approach to denoising the data is novel and has not been validated in this paper or others. Alas, I'm not sure why they bothered with the Swarm clustering since they take the contigs and map them against the SILVA reference database for exact matches. The justification for these two steps is not clear and needs to be clarified.

4. L154. "Two out of 35 control samples did not pass our sequencing quality thresholds". If I am right in assuming that this is previously mentioned 10,000 sequence threshold (L129), then the authors should be specific in stating that here. If there are other thresholds, then those should be stated at some point in the manuscript.

5. "dysbiosis" is used throughout the manuscript. This is a trendy piece of jargon that is pretty meaningless. Furthermore, their method does not really address the whole community, which is usually done when describing a dysbiotic state. This manuscript describes the quantification of single strains.

6. I do not believe that Peptoclostridium difficile is a valid name for Clostridium difficile. At this point, it appears that the most recent valid name is Clostridioides difficile (http://www.sciencedirect.co... "http://www.sciencedirect.com/science/article/pii/S1075996416300762)").

On 2025-08-01 15:43:59, user Gil Yardeni wrote:

A revised version of this work was published in July 2025, https://doi.org/10.1093/sysbio/syaf039

On 2017-11-03 07:27:26, user Stephane Boyer wrote:

The paper is now published in Research Integrity and Peer Review. Read it in open access here: http://rdcu.be/x3zm

On 2025-08-26 09:35:41, user Constant VINATIER wrote:

Feedbacks about your preprint : https://doi.org/10.1101/2025.08.13.669948

About registration: <br /> We could not find any information about the pre-registration of your study in the pre-print. Pre-registration involves documenting the hypotheses, methods, and/or analyses of a scientific study prior to its conduct (10.1073/pnas.1708274114; 10.1038/s41562-021-01269-4). If your study was pre-registered, we strongly encourage you to include the registration number in the pre-print, ideally in the abstract make this important information easy to retrieve, as this practice enhances transparency and reproducibility. If the study was not pre-registered, this should be acknowledged as a limitation. For future studies, we recommend pre-registering on an appropriate repository.<br /> About Protocol Sharing: <br /> We did not find the protocol for your study. If you have one, we encourage you to share it as supplementary material or deposit it in a publicly available repository such as the Open Science Framework ( https://osf.io ) or Zenodo ( https://zenodo.org/) "https://zenodo.org/)") . You can then include a statement in the Methods section indicating that your protocol is openly available (e.g., 'The protocol for this study is available at (link)/ in the supplementary'). Sharing your protocol will help readers better understand your study and enable them to reproduce it if they wish to test it.<br /> About the Statistical Analysis Plan Sharing: <br /> We did not find the Statistical Analysis Plan (SAP) for your study. If you have one, we encourage you to share it as supplementary material or deposit it in a repository such as the Open Science Framework ( https://osf.io ). You can then include a statement in the Methods section indicating that your protocol is openly available (e.g., 'The SAP for this study is available at (link)/ in the supplementary'). Sharing your SAP will help readers better understand your study and enable them to reproduce it if they wish to test it.<br /> About Deviations and/or changes<br /> We could not find any information about potential deviations or changes to the protocol in your pre-print. Since such deviations are common, if this applies to your study, we strongly encourage you to include a subsection titled Changes to the Initial Protocol in the Methods' section and discuss these changes as a potential limitation of your results. If any deviations occurred during your study, please specify them in this new subsection.<br /> About Data sharing / FAIR Data<br /> While we could access your data in OSF, we could not find any DOI. Sharing data is important for enhancing transparency and reproducibility. We encourage you to share it on a data sharing repository provided the data is not sensitive (Dryad, etc.) and include the Digital Object Identifier (DOI) in the Methods section.If you want more information about data sharing https://www.go-fair.org/ <br /> About Code sharing<br /> While we could access your code [interventioncontro_arm_1][code_location], we could not find any DOI. Sharing code is important for enhancing transparency and reproducibility, especially since it does not contain sensitive information. We encourage you to openly share it on a code sharing platform (Github, Codepen, CodShare, etc.) and include the Digital Object Identifier (DOI) in the Methods section. If you want more information about Code sharing https://fair-software.nl/ <br /> Comments :<br /> During the evaluation of your preprint, I noticed the presence of a post hoc analysis. I recommend creating a dedicated section that clearly describes any protocol deviations or changes from the initial plan, in order to enhance transparency and clarity.

On 2018-06-14 08:52:30, user ramleela wrote:

The figures and text in this looks very similar of the previous publications from the same group.

On 2025-10-21 02:08:44, user CDSL JHSPH wrote:

I enjoyed reading this preprint very much. I found the logical flow of the experiments quite smooth and elegant, starting with mosquitoes and the parasites and finally the hosts, as well as using the methods of sequencing and behavioural studies. I also appreciated the comprehensive approach that connects the efficiency of malaria transmission to the genetic and behavioural aspects between the host, vector and parasite. <br /> I particularly liked how you incorporated both mRNA sequencing and proteomic analyses to strengthen your conclusions, though it might help to clarify some figures (e.g., clearer axis labeling in hierarchical clustering and heat maps, discussing patterns in heat maps) and discuss potential experimental limitations, such as the frequency of proteomic sampling and how experimental settings, such as the single-bloodmeal design differs from natural conditions. <br /> Overall, this is an innovative piece of work which sets a foundation for future circadian and malaria studies.

On 2019-12-17 20:26:18, user R. Rocca wrote:

Given the expansion of ancient samples to 70, please republish the XLS table. Thanks!

On 2024-11-16 16:34:07, user Yi Liang wrote:

This preprint has just been published in Science Advances as follows: Li-Qiang Wang#, Yeyang Ma#, Mu-Ya Zhang#, Han-Ye Yuan, Xiang-Ning Li, Wencheng Xia, Kun Zhao, Xi Huang, Jie Chen, Dan Li, Liangyu Zou, Zhengzhi Wang, Weidong Le, Cong Liu*, Yi Liang*. Amyloid fibril structures and ferroptosis activation induced by ALS-causing SOD1 mutations. Science Advances 2024 Nov 1, 10(44), eado8499.

On 2018-11-07 15:23:37, user Tanai Cardona Londoño wrote:

I just had a look at this tool and put it to the test. It is amazing. Thank you.

I have a quick question... when you say the following: "In contrast, gene functions with extremely low homoplasy include sporulation, photosynthesis, and core processes such as transcription, replication, and protein synthesis".

Do you mean that these are more likely to have been inherited vertically?

The reason I ask is because one of the biggest controversies in the evolution of photosynthesis is whether the distribution of phototrophy has been driven by horizontal gene transfer or losses. The distribution of photosynthesis in bacteria is well known to be quite patchy, with only few phyla known to be phototrophic.

I have argue that even though the distribution of photosynthesis in bacteria is patchy, the phylogeny of many of the core proteins of photosynthesis indicate vertical inheritance with losses as the dominant evolutionary force, although at least one unambiguous cases of horizontal gene transfer is known of full phototrophy is known.

What is your opinion on this? Unfortunately, it is hard for me to understand how the homoplasy metrics were calculated.

Another thing:

I did a search using pfam, PF00124, a core photosystem protein (Type II reaction centre protein). This protein is known to be found in Cyanobacteria, Proteobacteria, Chloroflexi, Gemmatimonadetes, and in some of the newly assembled WPS-2 metagenomes.

My search retrieved 881 genomes with hits in 11 phyla of bacteria. No hits for WPS-2, which is not unexpected, leaving 7 new phyla not previously known to have phototrophy.

The sequences in this 7 phyla represented 1% of the total sequences, most, if not all of them likely to be “contaminated” genomes. I BLASTed all of these sequences: a few of these hit to photosynthetic eukaryotic algae, one genome classified as Fusobacteria had a sequence with 96% sequence identity to a gymnosperm! It is unlikely that these represent true horizontal gene transfer, and it is more likely to represent genomes with contaminating sequences. Something that is not uncommon at all.

I had experienced similar things before, see this for example: https://tanaiscience.blogsp...

Of course, 1% is relatively low, but how something like that could affect your analysis of patchiness and homoplasy, would 1% be considered negligible?

I know the evolution and distribution of these proteins pretty well, so it is easy for me to notice when something is off. I wonder if these phenomenon extrapolates across all protein families and genomes. In such case, 1% “contaminating” sequences, let’s call them false positives, of nearly 40 million annotations would be about 400 thousand sequences… what do you make of that? I know that you cannot control the quality of the available genome data, but something like that could result on overestimation of horizontal gene transfer occurrences in bacteria, for example.

I was just thinking that a word of caution or a bit of discussion regarding possible artifacts could be useful for non-expert readers who would want to use your tool, given that is so accessible and easy to use.

All the best,<br /> Tanai

On 2019-12-09 20:05:43, user Stefan Barakat wrote:

the peer reviewed version of our paper, now describing 22 patients with the recurrent homozygous mutation, is now published in Acta Neuropathologica<br /> https://link.springer.com/a...

On 2021-02-23 01:45:49, user so-called Scientist wrote:

Although this manuscript points to a lot of important issues reg. ADVANCED vs. ACCELERATED “brain aging” in the field of “brain age age prediction/estimation”, this manuscript ignores some fundamental publications discussing the fundamental difference between this issue. Early in the development of the “BrainAGE score” or “brain age delta”, it was very important to us (Cole, Franke, Gaser) to make a clear distinctions reg. “advanced” or “accelerated” brain aging! <br /> You may refer to the thoughtful & extensive explanations in those latest review articles…

Franke, K., Bublak, P., Hoyer, D., Billiet, T., Gaser, C., Witte, O.W., Schwab, M. (2020). In vivo biomarkers of structural and functional brain development and aging in humans. Neuroscience & Biobehavioral Reviews, 117:142-164. [doi: 10.1016/J.NEUBIOREV.2017.11.002]

Franke, K. & Gaser, C. (2019). Ten Years of BrainAGE as a Neuroimaging Biomarker of Brain Aging: What Insights Have We Gained? Frontiers in Neurology, 10:789. [doi: 10.3389/FNEUR.2019.00789]

Book chapter: Quantification of the Biological Age of the Brain Using Neuroimaging, DOI: 10.1007/978-3-030-24970-0_19, In book: Biomarkers of Human Aging

Cole, J.H. & Franke, K. (2017). Predicting Age Using Neuroimaging: Innovative Brain Ageing Biomarkers. Trends in Neurosciences, 40 (12), 681-690. [doi: 10.1016/J.TINS.2017.10.001]

On 2019-02-25 13:04:08, user Matthias M. Fischer wrote:

In his comment, Dr. Pouwels has expressed concern regarding the magnitudes of the correlation between rates of infection with antibiotic-resistant microbes and the use of antibiotics in the primary care vs. the hospital sector. He re-analysed a small subset of the data with a fixed-effects generalised linear model that is not further specified and compared p and R-squared values as a proxy of their biological significance.

In our view, the analysis he presented is inappropriate for two major reasons. First, the focus on a small subset of the data, in his case only 21 observations, leads to reduced statistical power, and thereby unreliable statistical estimates, which becomes apparent by the high standard errors and consequently higher p values Dr. Pouwels has reported.

Second and more important, by fitting only a simple fixed-effects model, strong confounding differences between the individual EU member states are missed. Important confounders which are not corrected for this way are for example the average yearly temperature of a country and its population density -- two factors that exert strong effects on antibiotic resistance rates (see references Bruinsma et al. (2003) and MacFadden et al. (2018) in our manuscript).

Additionally, the comparison of p values of predictor variables to assess their biological significance is debatable. It is well-known that statistical significance does not necessarily translate to biological significance, i.e. a higher or lower effect size of a predictor variable. Similarly, coefficients of determination, such as R-squared values, do not quantify the effect a predictor exerts on a dependent variable. For this reason, we instead consider the comparison of the partial regression coefficients of the different predictors (after properly controlling for confounding variables) the most meaningful way of quantifying biological significance.

As Prof. van Schaik correctly points out, we have only analysed the data for two bacterial species, which additionally are closely related to each other.

In case of the analysed datasets from the European Union, the exclusion of the data for the other three bacterial species was necessary. If one worked with data for two or even only one class of antimicrobial agents, the resulting statistical model would be strongly underpowered and not able to properly control for occurring confounding factors. Consequently, the estimates obtained by such a model would come with a high amount of uncertainty and would therefore be highly unreliable and potentially misleading.

We do agree with Prof. van Schaik that our results are not a final and definite proof, and we have explained the limitations of our approach in the discussion part of the manuscript. We have also made clear in the discussion that our analysis should be perceived as a starting point for further analyses of both theoretical and microbiological nature. Current ongoing research in our lab is aimed at compiling a more comprehensive dataset for more in-depth analyses also taking into account other bacterial species. Nonetheless, we believe that it is important to quickly disseminate our first findings to encourage further research and to provide a fresh perspective on this important topic. Further analysis will indeed reveal if hospital use of antibiotics is the main driver of population-level infections with bacteria resistant to other classes of antibiotics and with other pathogens as well.

Matthias M. Fischer, Matthias Bild

On 2016-09-15 13:24:39, user Susan Johnston wrote:

Now published in Philosophical Transactions of the Royal Society B<br /> http://rstb.royalsocietypub...

On 2021-12-17 09:24:12, user Jocelyn Étienne wrote:

Note that the movies are included, click "Data/Code".

On 2015-07-07 13:27:44, user Julien Roux wrote:

Is there a mistake with the legend of Figure 2C ("type of region")? As it is, the figure indicates a stronger enrichment of low p-values for open seas compared to sites nearby CGI and the lowest enrichment is seen for CGI. This is surprising and opposite to what you wrote in the main text (end of page 6). Did I miss something?

On 2019-04-05 07:17:21, user Able Lawrence wrote:

How relevant is a 3 ng/ml lower Vitamin D blood level in the real world. <br /> What is the point of heritability study that does not take into account skin colour and latitude and consequently access to UV light. How much would genetic factors add to a model that includes skin pigmentation and latitude.

On 2018-09-28 05:26:20, user Alex wrote:

Please note that the author list was updated in the published paper in Genome Biology. See https://genomebiology.biome...

On 2021-05-11 20:54:11, user Alex Hall wrote:

Would like to see supplementary materials on biorxiv when they are mentioned by the preprint.

On 2024-01-18 15:53:23, user Richard H. Ebright wrote:

1) The virus of this preprint, GX_P2V(short_3UTR), is a laboratory-generated gain-of-function mutant obtained by serial passage in primate cells.

Serial passage is a standard technique in gain-of-function research and enhanced potential pandemic pathogen research (see, for example, Fouchier's and Kawaoka's use of serial passage in ferrets to enhance mammalian transmissibility of avian H5N1 influenza viruses).

2) The claim that "outcomes from these tests cannot be applicable to humans" is false. ACE2 humanized mice are the standard experimental model, and best-available experimental model, for assessing pandemic potential of SARS coronaviruses in humans. If the authors actually believed the claim that "outcomes from these tests cannot be applicable to humans" they would not have performed the research, and they would not have written "This underscores a spillover risk of GX_P2V into humans."

On 2025-10-03 03:29:16, user Amoon Jamzad wrote:

???? Published version:<br /> This work is now published as: Jamzad, A., et al. MassVision: An Open-Source End-to-End Platform for AI-Driven Mass Spectrometry Imaging Analysis. Analytical Chemistry (2025). https://doi.org/10.1021/acs.analchem.5c04018

On 2017-02-20 21:26:05, user George Turner wrote:

The presence of salmonella in the corpses of Aztec plague victims argues that they weren't properly prepared and that you shouldn't eat them (scavengers and cannibals be warned), but not necessarily that they died from salmonella. You can be confident that the chicken that is left out on your counter, though it might be teaming with salmonella, actually died from getting its head lopped off at the processing plant, not from a bacterial infection.

Rotting bodies team with all kinds of dangerous bacteria that aren't necessarily the cause of death, and in a plague these bacteria can be transferred from body to body by the people handling the corpses.

On 2020-10-02 09:17:54, user Martin R. Smith wrote:

This sounds like a very useful package; are there any plans to add other tree distance measures beyond the problematic Robinson–Foulds, e.g. generalized RF distances? I'd be happy to share C++ implementations of some such distances if this would be useful.

On 2021-08-16 11:00:28, user Gregory Bix wrote:

This preprint has been published in the journal Life Sciences.<br /> https://www.sciencedirect.c...

On 2014-01-16 09:54:57, user Davidski wrote:

Actually, one of the most confusing things for me is the makeup of EEF.

The paper states that EEF might be around 44% Basal Eurasian, and possibly part European courtesy of an WHG-like population. But it's also estimated to be mostly Near Eastern.

This suggests to me that there's a third component involved, native to the Near East, and judging by Fig. 2A, perhaps it's a Near Eastern version of WHG, or in fact a Near Eastern component ancestral to WHG.

But as far as I can see, the paper doesn't say that anywhere, so my first impression was that EEF was a mixture of Basal Eurasian and an WHG-like population from southern Europe.

On 2017-07-06 18:56:35, user Fafner Normanko wrote:

This paper raises important safety issue for gene therapy application of CRISPR-Cas9. However, there are serious doubts about the results or interpretation. First of all, the authors listed Top-10 predicted off-target sites. But all genes are wrong! looking at the sequence they listed (supp. figure 3), you will not be able to find it in the genes! After careful inspection, the first predicted off-target is actually the "on-target" sequence for pde6b gene. For such a high-profile journal, you can't be so sloppy. This is not just a typo. I inspected them and they are all assigned to wrong gene. If you can't even get your on-target correct, how do you think people can trust your data? There are some genes are assigned to even wrong chromosomes! Supp fig3 panel b, listed herc1 gene on ch11. That gene is supposed to be on chr9. After this first figure, I don't even know if any other information reported here is correct!

I then went on to inspect Supp table 1-3. The authors listed all off-targets observed from the WGS. However, Pde6b pTyr347fs/c1041_1050CGTAGCAGAA is actually the on-target indel. and the author did not even notice this is their target gene? and listed it as one of the two off-target genes with mouse phenotype? The CRISPR-cas9 system is supposed to created Indel here! You simply did not repair it. You replaced the stop codon with the indel. I downloaded the raw sequence, and found that this specific deletion (CTGAGCAGAA)can not be found. Only by reading the authors previous paper, I figured out that they mean a 10 bp deletion but they don't even have the correct deletion sequence!

After seeing all these careless mistakes, I don't even know if they mislabeled the mouse or samples! It is hard for me to imagine CRISPR-case9 causes so many homozygous deletions in two independent mice (all right, it may happen in rare case for specific sgRNA like this one). And even if some of the mutations/indels are real, they may have nothing to do with CRISPR-cas9. For example, the authors see homozygous deletion in Pde9a gene in both animals. Do the authors consider the possibility that this deletion might be created by totally unrelated mechanisms and strongly selected for in vivo? since Pde9a and pde6b are paralogues. The easiest way to test if these are real CRISPR-cas9 off-target is to check these loci in treated cells in vitro. In that setting, you can check millions of cells to see if they do occur or do not occur. Maybe none of them is created by CRISPR-cas9 off-target. But during the embryo development, these mutations are created and strongly selected to compensate for something. I admit that in vitro does not speak for in vivo. But you can't just assume these mutations are generated by CRISPR-Cas9.

On 2017-07-10 14:25:52, user Luca Pinello wrote:

We want to clarify that the preceding comment from Fafner Normanko is a critique of the original Schaefer et al article (https://www.nature.com/nmet... "https://www.nature.com/nmeth/journal/v14/n6/full/nmeth.4293.html)"), which is the paper our biorXiv manuscript is a response to. That is, wherever Fafner Normanko mentions "this paper" or "the authors" in this comment (which is actually a word-for-word repost made by Xiaolin Wu (https://www.ncbi.nlm.nih.go... "https://www.ncbi.nlm.nih.gov/pubmed/28557981/#comments)"), this is a reference to the Schaefer et al. paper or authors and not our biorXiv response to their article.

On 2018-05-07 10:40:14, user Beatriz Apellaniz wrote:

Nice article.

I kindly suggest you to check out this reference:

doi: 10.1016/j.bbamem.2018.02.019

Best,

Dr. Beatriz Apellaniz

On 2020-04-23 10:47:43, user Dora Mahecic wrote:

Response to the main comments from the review by Andrew G York:

Comment 1<br /> I found the paper well organized and well written. I found the figures made clear, convincing arguments that their method greatly improves on the original iSIM design. I was impressed by the combination with expansion microscopy and particle averaging, especially the comparison to estimated speeds of STED and/or SMLM alternatives. I suspect their technique would also compare favorably to a normal-resolution microscope and a 2x larger expansion factor. I assume it's hard/annoying to expand 2x more? If the authors are comfortable doing so, I recommend adding this comparison (no additional figures, just a description of what they'd expect).<br /> We agree that it is important to offer comparisons to other methods yielding similar resolutions. The effective resolution improvement X is determined by the resolution improvement of the method (Xres) and the expansion factor (Xexp) such that X = Xres * Xexp. Therefore, in the case of iSIM (Xres = 2) and U-ExM (Xexp = 4-5), the effective improvement in resolution is in the range of 8-10-fold (X = 8-10). <br /> Achieving the same improvement is therefore possible on a standard diffraction-limited microscope (Xres = 1), if the sample has an 8-10-fold expansion factor (Xexp = 8-10), but raises several issues. Firstly, while methods for achieving larger expansion factors are available1,2, they are generally more complicated than the U-ExM protocol and have not been demonstrated for expanding multi-molecular complexes such as the centriole. Secondly, assuming a larger expansion factor Xexp is achievable, the field-of-view (FOV) would be reduced along each dimension by Xexp and would therefore require stitching together Xexp^2 individual images. This would in turn reduce the throughput by Xexp^2, and result in a 4-fold lower throughput than combining iSIM and U-ExM (assuming that both methods start with similar FOV sizes). The same applies to a spinning disk microscope, which could achieve a ?2 improvement in resolution and hence require an expansion factor of 5.5-7, and a decreased throughput by a factor of 2. <br /> Overall there are specific advantages to prioritizing Xres, since Xexp increases the physical sample size effectively reducing the size of the FOV. Furthermore, achieving Xexp beyond the traditional factor of 4-5 involves more complicated expansion protocols. On the other hand, additional advantages of increasing Xexp come from the fact that sample expansion also improves other optical (sectioning, aberrations) and mechanical (drift) features of the method. Therefore combining fast super-resolution techniques with moderate expansion is likely to provide the best of both worlds. <br /> A sentence addressing this issue has been added to the main manuscript lines 359-362, and a similar more detailed discussion has been included in the supplemental information lines 363-387.<br /> 1. Truckenbrodt, S. et al. X10 expansion microscopy enables 25-nm resolution on conventional microscopes. EMBO Rep. e45836 (2018). doi:10.15252/embr.201845836<br /> 2. Chang, J.-B. B. et al. Iterative expansion microscopy. Nat. Methods 14, 593–599 (2017).

Comment 2<br /> I don't fully understand how their optics work. Perhaps this is my fault; I have a decent background in optics, but a short attention span. If the authors want people like me to understand their optics better than I did, perhaps they can change the paper to convey this more completely. For example, it's not obvious to me exactly what effect the rotating diffuser has. What does the illumination look like with no diffuser, or with a static diffuser? How does the illumination change as the diffuser moves? Does motion of the diffuser change the position of each illumination spot, or the size, or the intensity? How fast does the diffuser have to move, compared to the galvo scanning? <br /> We thank the reviewer for bringing up this important question, which seems unlikely due to any lack of attention span.<br /> With no diffuser, the homogenization plane will not produce a flat-field but instead a highly inhomogeneous interference pattern making up a periodic array of spots1,2. The rotating diffuser serves to scramble the incoming wavefront and produce an extended partially coherent source. However, when the rotating diffuser is static, it produces a speckle pattern in the homogenization plane that is not homogeneous, but spatially random with respect to the interference pattern without the rotating diffuser.<br /> https://uploads.disquscdn.c...

Rotating the diffuser causes different, spatially random, scrambled wavefronts to be projected in the homogenization plane where the excitation microlens array (MLA) is located. In the front focal plane of the excitation MLA, each incoming scrambled wavefront will in turn produce spots with varying intensities, and might cause variations in the size and position of the spots (Supplemental Movie 2). However, if many different, spatially random, scrambled wavefronts are averaged over time (by a rapidly rotating diffuser), they will produce a homogeneous flat-field in the homogenizing plane and therefore a homogeneous array of excitation points in the front focal plane of the excitation MLA (Supplemental Movie 1, Supplemental Movie 3). <br /> How fast does the diffuser need to rotate to achieve homogeneity in the scanned spots? To characterize the scrambling speed of the rotating diffuser, we perform a back of the envelope calculation given the characteristics of the rotating diffuser and the imaging process. We then use the simulation platform and real data to quantify the relationship between the scrambling speed of the rotating diffuser and the variations in position, width and amplitude of the excitation points at different timescales. For a quick visual, please see Supplementary Movie 3, which shows how homogeneity of excitation points emerges experimentally as more and more wavefronts are averaged.

1. Back-of-the-envelope calculation<br /> This aims to estimate how fast the rotating diffuser averages out the incoming wavefronts during imaging. We characterize the rotating diffuser by its rotation speed ?, distance of the rotation axis from the optical axis r and a grain size d:<br /> Rotation speed ??6000 rpm=100 rps<br /> Distance from optical axis r?10 mm<br /> Diffuser grain size d?10 um<br /> Therefore we can approximate that as the diffuser is rotating, it will average out over n grains per unit time, and therefore produce at least n random wavefronts per unit time.<br /> n=2?r/d•??6.28•10^5 s^(-1)<br /> This is a conservative estimate of the scrambling rate, since changing sub-grain position on the diffuser is likely to produce a differently spatially distributed wavefront.<br /> Now, given an imaging frame rate f and assuming that on the sample each point needs to scan a distance s, we can approximate how many scan positions p this requires given a diffraction limited spot size on the sample s_PSF.<br /> Imaging frame rate f=10-100 Hz<br /> Scan distance s?10 um<br /> Diffraction limited spot size s_PSF?0.25 um<br /> Number of scan positions on sample p?s/s_PSF ?100<br /> Finally, we can estimate the number of wavefront iterations over which each point is averaged at each scan position on the sample as N:<br /> N=n/(p•f)<br /> At the fastest imaging rate f_max =100 Hz this results in N_max?62.8 iterations<br /> At the imaging rate used in the majority of this work f_real=10 Hz this results in N_real?628 iterations<br /> We would like to highlight that these numbers represent a purely technical limitation, and that higher scrambling rates can be easily achieved by increasing the distance of the axis of rotation of the rotating diffuser from the optical axis, finding a rotating diffuser with a faster rotation speed or smaller grain size, placing two rotating diffusers in series but rotating in opposite directions2 or switching to speckle reducers with higher operating frequencies such as the Optotune Speckle Reducers sold by Edmund Optics (https://www.edmundoptics.co... "https://www.edmundoptics.com/f/optotune-laser-speckle-reducers/14335/)"). Nevertheless, we thank the reviewer for helping us improve the characterization of the setup and highlight this important technical consideration.

2. Simulation <br /> To test whether the numbers of iterations from the calculation are sufficient to provide homogeneous spots during scanning, we use our extended simulation platform to address how the position, size and intensity of the spots is changing when averaged out over different numbers of iterations. <br /> To test whether the numbers of iterations from the calculation are sufficient to provide homogeneous spots during scanning, we use our extended simulation platform to address how the position, size and intensity of the spots change when averaged over different numbers of iterations. To do this, we generated 8000 random wavefronts using our extended simulation platform, before bootstrapping over different numbers of iterations and examining how the intensity of the same point varies between the different averages and their realizations. Specifically, we measured the position of the maximum of each peak, its FWHM and maximal value representing the amplitude, and compared the same parameters across 10 different realizations of bootstrapping together a varying number of iterations N. Each realization contained ~90-110 excitation spots. A visualization of how the flat-profile is built up by averaging over many realizations in the simulation is shown in Supplementary Movie 1.

https://uploads.disquscdn.c...

We then quantified how these parameters varied between 10 different realizations, by computing their difference for each excitation point between the 10 different realizations for each N. Plotting the variation distributions allowed us to measure their FWHM and reported those values as function of the number of iterations over which the illumination is averaged out. Similarly, we can study how the intensity of a single point varies between different scrambled wavefronts (without temporal averaging). All of these results are now reported in the Supporting information and compared with the experimental results.

1. Experimental results<br /> Since the rotating diffuser rotates too fast to capture the individual wavefronts corresponding to different positions of the diffuser, we manually rotated the diffuser by random amounts to acquire 2064 images of the resulting scrambled wavefronts, analogous to the simulated data. How the excitation spots change at different positions of the rotating diffuser is represented in Supplementary Movie 2. We then repeated a similar analysis as for the simulated data, by comparing the variation in spot position, size and intensity by bootstrapping over different numbers of iterations. This is represented in Supplementary Movie 3.<br /> https://uploads.disquscdn.c...

By measuring the FWHM of the variation profiles, we could study how the spot localization, width and amplitude varied as function of the number of iterations. Specifically, we measured the subpixel localization of each spot by fitting it to a 2D Gaussian profile, from which we also extracted the FWHM of each spot. There were generally ~472 spots in different frames and bootstrapped realizations. The amplitude was measured by taking the raw pixel value at the peak location. <br /> https://uploads.disquscdn.c...

Similarly, by not bootstrapping over multiple iterations, we could compare how a single point varies between individual scrambled wavefronts.<br /> https://uploads.disquscdn.c...

The results show that the simulation is conservative compared to the real data. This could be because the simulation is performed in one dimension, while the real data is two-dimensional, and that averaging over an additional dimension could produce better results. Nevertheless, the simulated and real results show that averaging over an order of magnitude of 10 iterations produces excitation spots with <20% variation in intensity, while averaging on the order of 100 provides <10% variation in intensity. Interestingly, the values appear to plateau at ~2-3% which could be due to the limited size of the simulated and experimental datasets, or suggests that averaging out further does not bring additional improvement to the homogeneity. <br /> The variation in spot localization and width also decreases as the excitation is averaged over more iterations. The plotted variations in localization and width are represented before magnification (x116). Therefore, on the sample these represent ~10 nm variation in localization and width, which does not compromise the ability to focus the excitation to a diffraction-limited spot. In fact, the slight variation in localization of the excitation spot might be beneficial in reducing the striping artefact often present in scanning methods. <br /> We briefly summarized this analysis in the main manuscript lines 194-198 and a similar more detailed discussion has been included in the supplemental information lines 221-334 and Supplemental Figure 4.<br /> 1. Zimmermann, M., Lindlein, N., Voelkel, R. & Weible, K. J. Microlens laser beam homogenizer: from theory to application. 666302, 666302 (2007).<br /> 2. Voelkel, R. & Weible, K. J. Laser beam homogenizing: limitations and constraints. 71020J (2008). doi:10.1117/12.799400

Comment 3<br /> For another example, it's not obvious to me what the second flat-fielding MLA is doing. Naively, it seems to me that I could remove it from Figure 1i without changing the beam path, but presumably I'm wrong. Perhaps fine details of the optics may not be the point of the paper, but if they are, I'd like to see more details. I apologize in advance if these details are present, and I simply missed them.<br /> We thank the reviewer for pointing out this lack of clarity. Briefly, the second MLA serves to cancel the quadratic phase curvature introduced by the first MLA1,2.<br /> In detail, the primary components of a Köhler integrator are a collimating lens, a pair of microlens arrays (MLAs) and a Fourier lens1,2. The collimating lens serves to collimate the light from the inhomogeneous light source. The first MLA takes the incoming collimated beam and samples the different parts of the angular spectrum through the individual microlenses. Each microlens channel serves as a parallel Köhler illumination channel for different sections of the angular spectrum of the beam. The second MLA, identical to the first one and positioned one focal length away from the first MLA, serves to cancel the quadratic phase curvature introduced by the first MLA. The Fourier lens then combines the light from the different microlens channels at its front focal plane, causing any variations in the spatial and angular distributions of the light source to be averaged out into a flat-top beam. <br /> For incoherent light sources, this would be sufficient to produce a homogeneous flat-top profile. However, for coherent light sources such as lasers, the homogenization plane would produce an inhomogeneous interference pattern. Therefore a focusing lens and a rotating diffuser are needed to scramble the incoming light and create a partially coherent extended source. <br /> We added a sentence further describing the Köhler integrator to the manuscript lines 93-96 and an extended description in the supplemental information lines 22-37.<br /> 1. Zimmermann, M., Lindlein, N., Voelkel, R. & Weible, K. J. Microlens laser beam homogenizer: from theory to application. 666302, 666302 (2007).<br /> 2. Voelkel, R. & Weible, K. J. Laser beam homogenizing: limitations and constraints. 71020J (2008). doi:10.1117/12.799400

Comment 4<br /> I found the first video striking and beautiful. The second video, in contrast, emphasizes the striping artifact in a way I found jarring. Your stripes are certainly improved compared to my iSIM, but I suspect this movie will alarm at least some of your readers. On the other hand, I applaud your honesty in showing both the good and the bad. If your iSIM is like my iSIM, the highly visible stripes are due to out-of-focus objects in a thick sample. If so, I recommend adding a brief discussion of striping to the text, to manage expectations for your reader. It might also be worth (briefly) discussing methods to mitigate this artifact (for example, extra scanning mirrors like the Visitech Ingwaz, or computational methods).<br /> We agree with the reviewer, that striping artifacts should be better described as well as how to mitigate them. <br /> iSIM imaging can produce substantial striping artefacts due to its scanning mechanism, especially in thick samples with significant out of focus light. While careful alignment can diminish the intensity of the stripes, there are also mechanical solutions that mitigate the striping on the sample, or computational tools for filtering out the effect during post-processing. For example, the commercial Visitech Ingwaz system introduces extra scanning mirrors to fluctuate the position of the beam and hence reduce the striping artefact. Furthermore, a similar effect might be introduced by mfFIFI due to the slight fluctuation in the localization of the excitation spots, although this might not be sufficient to fully overcome this effect.<br /> We have added a similar discussion to the supplemental information lines 353-362.

Finally, I believe your method is novel, inventive, and potentially commercially important. Therefore perhaps you should patent your method. If you choose to file a patent, I recommend disclosing this (reasonable) conflict of interest.<br /> We thank the reviewer for this comment and have revised the conflict of interest section accordingly, found in the manuscript linse 665-669.

On 2020-07-19 23:08:46, user Henrique Sommer Vianna wrote:

I think famotidine acts as imunomodulator in the th1/th2 ballance, IL-6 production and cytokines cascade!

On 2020-08-20 15:28:48, user Yina Du wrote:

Please welcome to checkout our featured toolset "Lung at a glance" ( https://research.cchmc.org/... ). Or stop by LGEA Web Portal (https://research.cchmc.org/... ) for more exploration!

On 2019-07-14 23:04:04, user Hyo an wu wrote:

According the data of your research, CDNF increased the calcium transient. This effect caused any disturbance in the ECG waves, intervals and amplitude?

On 2019-11-29 13:30:20, user Norman Zielke wrote:

E2F-dependent genetic oscillators control endoreplication https://www.ncbi.nlm.nih.go...

On 2017-09-06 12:28:00, user Rafael Maia wrote:

For a reproducible example of how to implement the suggestions found in the manuscript, see: https://github.com/rmaia/ms...

On 2019-06-27 07:02:36, user Joe Li wrote:

This paper has been published in Environment DNA https://onlinelibrary.wiley...

On 2020-12-05 11:19:41, user Soumendranath Bhakat wrote:

Dear Authors,

The occurrence of Tyr inhibited conformation (H-bond interaction between Tyr and Asp) has been predicted by Bhakat & Söderhjelm (https://www.biorxiv.org/con... "https://www.biorxiv.org/content/10.1101/2020.04.27.062539v1)"). Please cite the original article. You reinvented a measure of flap opening which takes the distance between Tyr-OH and Asp-CG but it can be deceptive as it depends on the torsional degrees of freedom associated with Tyr side-chain. A more stable measure is to take CA distance between flap tip residue and catalytic aspartic acids which has been discussed in the following articles (similar distance metrics have been proposed by Caflisch and others):<br /> 1. https://www.biorxiv.org/con...<br /> 2. https://pubs.rsc.org/en/con...

Could you please discuss how your distance metrics is better compared to the one mentioned in those articles with proper citation to them. Finally, Bhakat & Söderhjelm proposed a generalised theory of flap dynamics in pepsin-like aspartic proteases which was completely ignored in the discussion section of this pre-print. I think most of the outcomes of this paper confirmed their hypothesis. A proper discussion surrounding that will be a good take-away for the community.

Improvement:

Maybe a free energy plot showing distance between Tyr-Trp and Tyr-Asp H-bond interaction during simulation.

Best regards,<br /> Soumendranath Bhakat

On 2024-10-08 09:43:09, user Bruno Cenni wrote:

Very nice and comprehensive dataset and overview across almost all BTKi. A note with regards to the data in Table 2 and Figure 4. For remibrutinib a BTK potency of 1.3 nM as “Kd or IC50” is listed. While the data is correctly referred to Angst et al 2020, this manuscript lists the IC50 for biochemical BTK enzyme inhibition. The same Angst et al 2020 publication also includes the Kd of remibrutinib for BTK (measured in the same assay all the others in the present manuscript) which was 0.63 nM. This is the value that should enter Table 2 and Figure 4.

On 2017-11-13 22:01:35, user Rebecca wrote:

Cool! But how do you know loss vs independent gain? "Hundreds of lineages across animal phylogeny have secondarily lost larval forms, instead producing offspring that directly develop into adult form without a distinct larval ecological niche"

On 2018-06-14 13:44:50, user GUILLAUME GAUTREAU wrote:

Little typo in algorithm 1, line 9: last parenthesis is not at the correct level

On 2013-11-22 03:37:05, user Jacob G Scott wrote:

This paper has just been accepted by PLoS Computational Biology - look for it there soon...

On 2019-03-26 14:35:32, user Adam Freedman wrote:

for anyone wanting to follow progress on this paper, I'll be posting updates via @afreedman405

On 2020-12-18 13:49:48, user Karen wrote:

Beautiful paper! I think there may be some confusion on the VM6 glomerulus. This glomerulus was renamed VC5 in the Bates paper and continued here. The Bates paper noted that there has been confusion on VM6 in the past, presumably due to its poorly defined morphology with nc82 staining. However, the VC5 that Richard Benton has named (aka Ir41a ORNs) is relatively small and corresponds better to VC3m (Li Volkan 2016 refer to it with both names).

My lab has recently identified a drive that identifies a previously unstudied 4th ac1 ORN and this ORN targets the "classic" VM6, which by morphology, position and size matches the glomerulus you are calling VC5. GCaMP imaging shows that these neurons have a different response pattern than the Ir41a VC5/Vm3m ORNs. Several papers studying ORN lineages using MARCM and other clonal analysis have found that the VM6 ORN develops from the same lineage as the three previously known ac1 ORNs, which makes sense since all four are in the same sensilla and presumably come form the same SOP (Endo Hama Nat Neuro 2005, Li Volkan Plos Genetics 2016, Chai Benton Nat Comm 2019).

For consistency in the literature, I would think the following make sense based on morphology, clonal analysis, and historical references:

Or35a ORNs- target either VC3 (Couto 2005, Grabe 2015/2016, Silbering 2011) or VC3l (Fishilevich 2005, Li 2016)

Ir41a ORNs- target either VC5 (Grabe 2016, Silbering 2011, Li 2016) or VC3m (Li 2016)

4th ac1 ORNs (our driver- that we can share)- target VM6

Happy to discuss further if you'd like!

On 2022-01-15 18:50:31, user Tunefish wrote:

Q:Why syrian hamster are choosen for these kinds of experiments?

On 2020-07-22 11:42:37, user Inci Çetin wrote:

The article addresses a very current topic. The authors underlined that EKC and transportation will be more important because production cost will be higher especially in the pandemic period.<br /> The authors supported their work with six statistical methods and the article discusses the issue in detail. The data range used by the authors is quite sufficient.

On 2020-05-29 11:15:25, user M Irfan Qureshi wrote:

Excellent Article!<br /> It complement many assumption expressed in the article below:<br /> Qureshi, M. Irfan and Asim, Mohammad, Probing Occurrence and Possible Roles of New Insert in Spike Glycoprotein of SARS-CoV-2 (May 15, 2020). Available at SSRN: https://ssrn.com/abstract=3... or http://dx.doi.org/10.2139/s...

On 2019-04-09 18:13:53, user Peter-Bram 't Hoen wrote:

Very interesting article on the tissue- and age-dependence of skewed X-inactivation. Results are largely in line with our recently published paper: https://www.nature.com/arti.... Here we used RNA-seq data from blood of trios to quantify degree of skewing of X-inactivation. In this paper, we explain that the observed skewing pattern is likely to be caused by stochastic nature of the X-inactivation process at an embryonic stage where only a limited number of precursor cells gives rise to the cell population in a given tissue. This explains correlation between fat and skin (common precursor cells), and no correlation between fat / skin and blood. It also may explain why the degree of skewing differs between tissues, as the size of the pool of precursor cells at the stage of X-inactivation may differ between tissues. We have not detected the age-dependent effect, likely because we included mostly individuals <55 years of age.

Peter A.C. 't Hoen, Radboud University Medical Center Nijmegen, The Netherlands<br /> Twitter: @pacthoen

On 2020-06-26 10:15:50, user Ersa Flavinkins wrote:

Major issue with the article: the vector, the pcDNA3.1-N-myc/C-C9 vector, is not found nor availible from catalogue in anywhere. All the ACE2 proteins are stained with anti-C9 antibodies--indicating that the cloned part is not the entire mRNA.

The original specification of the c-myc/c9 vector was stained by the anti-c-myc antibodies on the cell surface--so there is an additiona signal peptide in fromt of the c-myc tag in the vector.

no pcDNA3.1 vector have an AgeI site and XM_017650263.1 is not cut by either AgeI or Acc65I. As the human, civet and rat ACE2 gene is specified to have their signal peptide removed before cloning into their vector, the vector must carry it's own signal peptide--which is before the c-myc tag as the original thesis at ref.55https://www.ncbi.nlm.nih.gov/pmc/ar... and ref.34 https://www.ncbi.nlm.nih.go...

specified the staining of the cells via antibodies targeting the c-myc tag on the N terminii of the ACE2 receptors.

This leave all the receptors--the Human,Civet and the Rat--with an N-terminal C-myc tag. and the Ferret badger, Rhesus, Raccoon dog, Hog badger, Free-tailed bat, Rabbit, cat and dog ACE2 receptors may potentially contain parts of the signal peptides themselves or even the entire signal peptide. The Rs bat and pangolin ACE2 receptors were cloned into an unknown vector and there is no way of telling whether the Signal peptide, c-myc tag or other AAs were retained or not. However, as these were all marked as C9 tagged on the C-terminus, the exact cloned part must not include the C-terminal stop codon or other parts of the mRNA since the natural Stop codon will prevent C9 tag expression.

There is no indication of the N-terminal clone site for the 2 ACE2 proteins, but the Human, Civet and Rat ACE2 is specified to have the signal peptide sequence removed. and therefore an additional signal sequence must be included before the C-myc tag in the vector to enable cell surface display.

As the article specifies that the ACE2 proteins expressed from such vectors have a "N-terminal c-myc tag and a c-terminal C9 tag", the tage expressed as specified have serious issue with steric clashing with the other S1 RBD monomer and therefore downplaying the Human, Rat and Civet ACE2--this may be even more severe with the other ACE2 and the exact N-terminal status of the Rs and pangolin ACE2 receptor is impossible to tell. Over all, this experiment is heavily contaminated and there is no way to actually deduce the results by just their method section alone. As no published vector available offers simultaneousy the N-myc and C-C9 tagging capability in the protein product, it may or may not be the same vector as specified before.

At best, it may downplay the ability of hACE2 to mediate entry with the PP assay by steric clash with the Tag and potential AAs in front of them--indicating an intentional overplay of Rs bat and pangolin ACE2 receptor by handicapping the rest with a bulky protein tag and a potential antibody binding to the tag, all of which clashes with the rest of the S glycoprotein and significantly decreases the entry efficiency, at worst--if the specified N-myc/C-c9 vector is the same as the vector described before, it mean that none of the PP assays are trustable as actual, unbiased data.

Notably, the PP assay result described here is in conflict with another paper https://www.biorxiv.org/con... using the exact same protocol but specified a different N-terminal tag--the HA tag, again on the N terminus of their ACE2 proteins. Notably, the Rs bat and Rat receptor affinities, as well as the Feline and pangolin receptor affinities, as by PP assay, were inverted in the 2 publications. As well as the Feline and Rabbit receptor affinities--despite the feline and rabbit are specified as being tagged using the same protocol in both publications--c-myc in this and HA in the other.

Unless the exact cloning sequences of the vectors and the inserts are published, neither publications can be used as an exact indicator of the true affinities of the ACE2 to the S glycoprotein, and none of the publications may be used as a true indicator, in isolation or in tandem, of the true affinities of animal ACE2 to the SARS-CoV-2 Spike glycoprotein.

On 2020-06-30 20:00:26, user Manish Kumar wrote:

Fig 1: Please correct the color order of those dots. Red and yellow dots should be flipped on one side of the objective. An object farther from MO1 will get imaged closer to MO2.

On 2023-10-26 06:27:29, user Tom Hitch wrote:

You may wish to use the up-to-date taxonomy for these taxa. Prevotella copri was reclassified as Segatella copri last year; https://lpsn.dsmz.de/specie...

On 2025-06-30 15:30:58, user John McBride wrote:

Found the code, thanks! https://github.com/themusiclab/animal-sounds

On 2016-07-21 14:38:29, user bioRxiv wrote:

We have not deleted any comments and have not found any in our spam filters. Please feel free to comment again.

On 2025-04-25 15:51:05, user Sandra Shefelbine wrote:

We thank you for the comments. We are revising this draft to reflect your comments.

On 2021-05-07 14:01:00, user Anonymous reader wrote:

The diet (table SI 8) includes many mites (4 orders) and... krill! These OTUs should probably be filtered out and procedures used for the taxonomic identification of sequences might be improved somewhat :)

On 2023-05-16 23:37:19, user MICR 603 wrote:

Summary.

Since the emergence of SARS-CoV-2, the causative agent of the disease COVID 19, various vaccines and treatments have been developed that have been shown to be effective in reducing risk and severity of clinical outcome. Some limitations of current COVID19 treatment options is the inconsistency of their therapeutic efficacy across strains as well as possible unknown off-targets. To address these concerns, the use of llama-derived nanobodies (Nbs) has become of interest. Nbs have been shown to have a high affinity and specificity for targets, therefore decreasing risk of effects coming from possible unknown off-targets. In this study, llama-derived Nbs capable of neutralizing several SARS-CoV-2 strains were identified. In the In vivo model, Nbs were indicated to effectively induce protection in several lung tissues including the brain. These findings suggest Nbs as possible therapeutic agents for protection and treatment of SARS-CoV-2.

Positive feedback.

This paper looked at the exciting research area of advancement upon monoclonal antibodies through Nbs. The researchers did a thorough job of explaining the genomic structure of SARS-CoV-2 as well as the interaction occurring during the initial attachment phase (lines 58-66). An exciting advancement of this study was the identification and characterization of SARS-CoV-2 neutralizing Nbs. These findings were made more impressive with their consistency found among varying strains as well as in both in vivo and in vitro design models. The use of several strains is important as individual strains can have very different effects and outcomes. The figures were nice with the appropriate size (not too small) being used for readability and the layout was not overwhelming with not too many figures being placed together (example Figure 3). I also liked the color scheme used as even though similar ones were used, varying shades were used to clearly contrast such as magenta as opposed to a lighter pink (example Figure 3 D). I especially liked Figure 10 for its ability to encapsulate a lot of information. The authors did a good job of explaining their research to those outside the field. <br /> The methods used to derive antibodies was well explained and will be helpful for those who would like to expand upon the research using this methodology.

Major Concerns

Different sources of S protein were used for different immunization points. Example the first two immunizations used were from one source and then third immunization is obtained using S protein from a different source. Moreover, they mention that the S protein parts encoded on expressed vectors are slightly different, how? (page 5 line 110) Authors should provide more detail into plasmids used, a table of recombinant proteins being used would be good. This is important as it probably represents the variability observed in Figure 2 when showing S protein binding of nanobodies.<br /> For Figure 6, an interpretation was not given in the discussion. It was mentioned that the Delta variant was not able to be neutralized by any of the non-RBD binders (pg. 11 line 279), but the researchers did not revisit this to share any hypothesis as to why this might be happening.

In Figure 2, it might be good to see raw data and a correlation coefficient (R^2) to see how good the fit is. It might be helpful to include Km in the figure instead of just in a table.

Proper positive controls in protection experiments are missing. For example, protection against various SARS-CoV2 variants with new nAbs could be compared with existing tools, e.g., mAbs used in clinic and/or current antivirals. Otherwise, it is hard to know whether the new tools are better than existing ones.

Minor concerns

The researchers briefly discussed ways in which their current work could be expanded upon (line 443-446), but did not mention the current limitations of their study. Discussing limitations is helpful for the reader in better understanding the results from the paper. <br /> What are some other routes that nanobodies can be introduced into the mouse besides intranasally? Will this route translate to humans?<br /> Full organs were used for calculating SARS-CoV2 titers. Was different localization of the virus seen in different areas of the brain? It might be interesting to discuss if they saw any differences and suggest this as a future direction. https://www.nature.com/arti...

Figure 2 A-data points for NB-45 are difficult to see. Perhaps the data and the fits could be divided into classes instead of all in one figure.

Figure 4 B, it is not made clear why the concentrations of nanobodies being used was chosen. Example NB-39 and Nb-43 is at 10 ug while the other nanobodies are administered at 20ug.

It would be good to be more clear about the criteria for mice to be euthanized (such as the amount of weight needed to be lost). Some of the weight loss seems to be small (according to our standards) for euthanization.

Figure 4 legend could include the amount of mice (assume 5), but this is not clear.

In Figure 2, the variability of Nbs binding to Spike protein is very different (2A.) This is in contrast to the little variability noted between Nbs binding to RBD (2B.) This finding is not discussed in the paper.

This may not need to be expanded upon, but I was curious why 4 days post-challenge was chosen to harvest tissues to evaluate the effect of nanobodies on virus titers (line 716 pg.28). It would be good to compare this time point to other time points. Do you have samples from surviving mice that you could look back at?

In Figure 5, are the statistical values noted in Figure 4 also supposed to apply to Figure 5? Also, the significant difference between treatment groups in the same tissues with different letters is noted in figure legend 5, but it is somewhat confusing what is meant. More clarification in the figure legend would be helpful.

The discussion portion did not reference all figures that were discussed. For example, the Biliverdin competition assay was mentioned, but not properly referenced (page 15, line 378).

Animals only have clinical signs and cannot have symptoms as is described in (line 716). A clear distinction should be made between symptoms and clinical signs. https://jamanetwork.com/jou....

Figure 5, you could add a figure for each tissue and connect data points by mouse for each nanobody. This will help to see if specific mice have a consistency in nanobodies across tissue types.

Figure 9, orientation of protein is flipped frequently (Figure 9A). Some papers may require the structure be kept the same throughout the figure.

S1D, a caption stating what genes or products are being amplified (like a schematic) would be helpful.

S3, states that length of antibodies ~133 nucleotides. Why did they amplify 700 nucleotides? It should be 400 nucleotides only.

In SF. 5, maybe determine a better way to present Western blot data and revisit to describe why there are dots and not strong bands. Could WB be quantified using something like densitometry?

On 2016-04-07 07:49:17, user Andrew Page wrote:

Very poor choice of name since there is already a bioinformatics tool called artemis with over 2000 citations. <br /> http://europepmc.org/abstra...

On 2019-06-20 17:16:54, user Taj Azarian wrote:

Great manuscript. I have been trying to replicate and the one piece of information I found missing was the gDNA concentrations in the controls and the depleted samples. Before attempting qPCR, I was using this to determine how successful the extraction and depletions were. Thanks!

On 2020-01-30 17:29:39, user K. Amikura wrote:

All your feedback is really welcome!

On 2021-03-24 21:58:50, user JL wrote:

Where is the phase III data? How long can it take to make results public?

On 2022-08-10 18:59:43, user Sam McBrayer wrote:

Very interesting study!

On 2019-08-01 17:42:54, user Valentina Unakafova wrote:

Now published at https://www.frontiersin.org...

On 2021-04-26 14:18:55, user Katsu Murakami wrote:

rRNA transcription occupies ~70% of total RNA synthesis in rapidly growing E. coli cells. So I'm wondering observed reduction of rRNA level after Rif treatment can be explained by simple reduction of rRNA synthesis instead of rRNA degradation.

On 2015-12-15 02:03:47, user Philippe Henry wrote:

Hey guys,

Great work, it's quite something to gather 300+ accessions and stitch NGS data together like that! Epic graphics too, props. I noticed on the high def image posted on fig share that Chemdog91 appears to be duplicated in the tree, both times it is placed in the broad leaf drug type. My understanding is that chemdog or chemdawg 91 is "sativa" dominant and displays mostly narrower leaves. In my latest analyses it clustered with other "sativa" dominant hybrids: https://peerj.com/preprints...

Another very interesting finding is found on fig 3, which seems to be in disagreement with findings in the above study and Sawler et al's paper.

Besides that I would say this is a great addition to the literature, a very exciting read with a wack load of cool inference.

Best,<br /> Philippe Henry

On 2021-03-07 19:03:47, user Elisabete Morais wrote:

We are a group of PhD students from ITQB who used this paper for a journal club discussion during a course presentation. Overall we enjoyed reading the manuscript. Kropocheva et al. study discloses the Kurthia massiliensis Argonaute (KmAgo) activity mechanism by showing its relaxed specificity for nucleic acids mainly towards RNA targets. They demonstrate that KmAgo is a unique programmable nuclease that can potentially be used in a wide range of nucleic acid biotechnological applications, such as for precise nucleic acid detection and cleavage. As the in vitro results show promise, it would be interesting to address the in vivo validation.

On 2021-10-25 18:36:26, user Michael Matthew wrote:

This was a great examination of the factors affecting ecosystem food webs. I have one question about predator-prey balance. While a major concern is the removal of feral donkeys and similar invasive megafauna, you also mentioned the importance of maintaining predator populations. Regarding optimal food ecosystem and web structure, what are the most effective methods of maintaining predator populations and introducing supplementary predators if needed? Does this depend on predator-prey relationship, time of year, or biome?

On 2022-05-09 21:08:51, user Amar Khan wrote:

Insightful. Single-molecule magnetic tweezers spectroscopy is an exciting prospect

On 2018-07-29 09:18:13, user Chenfu Shi wrote:

Hi, just a quick question. Does setting the number of workers to more than 2 threads improve performance(without splitting the files)? Because it talks about parallel processing but I feel that's more for downstream analysis so I'm a bit confused...<br /> Thanks!

On 2019-08-28 21:54:47, user Hanon Mcshea wrote:

What about "evolve" or a different "e" word besides "enslave," to describe the third step of the eukaryogenesis process? "Evolve" would indicate the point at which Darwinian evolution begins to direct the process.

On 2022-10-22 02:13:33, user Martina Kathryn wrote:

This was a great paper, very informative comparisons and analysis done. The only source of confusion was with the supplementary figures 1A and 1B. You stated that, "The number of VSGs in a sample did not correlate with either the number of reads aligned or the number of parasites in a sample 1A & B)" which I agree with but you added on to state that this was "suggesting that sampling of each population was sufficient" which I didn't understand. Also the labeling of the x-axes for figures 4B and 4C was really confusing. 4B- I interpreted the label as though this measurement was done in only one mouse, but then this wouldn't be possible because the mouse would have been killed on day 10 and measurements couldn't have been done on day 14. Not until I read the text section. Maybe I'd advise that you add n=4 to this figure to indicate that 4 mice were monitored for each tissue. This was the same case for 4C. Ideally, one is supposed to look at the figure and get all the necessary information from it without checking the text part of the results for more information about what the figure is communicating.

On 2020-09-14 16:54:33, user Morgan Price wrote:

Seems solid, but I was a bit disappointed by the evaluation. They declare success if they find all the proteins that can be annotated as something by homology, and find as few other proteins as possible. But we do actually have other information indicating that some of the hypothetical proteins are likely genuine (proteomics, ribosomal profiling, conservation analyses ala CRITICA; even RNASeq data provides a significant constraint).

On 2025-05-05 08:19:56, user Tom wrote:

Hi,<br /> nice model! :-) The concept of "DPC" looks rather similar to what we refer to as "missingness model" in 10.1093/biostatistics/kxaf006.<br /> Best,<br /> Tom

On 2018-09-10 18:27:16, user Bin wrote:

This is reasonable since a structured 5' UTR will make transcript more stable.

On 2020-09-01 00:53:51, user Jason Paquette wrote:

Misquote from referenced paper #16. Experiments were acute and not "6090 min" long. Quote from abstract was "60-90 min", referring to the duration of washout periods between stimulation trials.

"It is not surprised that the rats could survive for such a long time with a stable micturition reflex under repeated stimulation and cystometry recordings. Indeed, there was a report that the rats survived in a good condition for 6090 min (4 days) under the urethane anesthesia with the repeated stimulation and recordings [16]."

On 2017-03-08 20:34:01, user Jean Manco wrote:

Discrepancy between tables re sample KON3 mtDNA. T2b vs T2c1.

On 2019-06-15 21:21:43, user ebarthelmess wrote:

HI folks - we'd love any feedback on this preprint!

On 2024-01-19 03:55:33, user Pamela Bjorkman wrote:

This paper was published as: Cohen, AA, Gnanapragasam, PNP, Lee, YE, Hoffman, PR, Ou, S, Kakutani, LM, Keeffe, JR, Wu, H-J, Howarth, M, West, AP, Barnes, CO, Nussenzweig, MC, Bjorkman, PJ (2021) Mosaic nanoparticles elicit cross-reactive immune responses to zoonotic coronaviruses in mice. Science 371: 735-741. PMCID: PMC7928838 doi:10.1126/science.abf6840

On 2017-09-29 05:37:48, user JH Kang wrote:

Very interesting work! <br /> Btw, how would you exclude calcium? Human TRPA1 is not a good receptor for H2O2 but is potentiated by intracellular Ca2+.

On 2023-11-14 16:49:20, user James Mallet wrote:

Congratulations on this provocative paper which I read with great interest.

However, I have some questions about the meaning of the results. Your paper suggests that previously, the prevailing belief has been that there is more hybridization, and therefore more gene flow between species, in plants than in animals. However, your preliminary discussion suggests that this is actually an artefact of “rely[ing] on morphological traits to arbitrarily define species (16),” where ref. 16 is Mallet 2005 in TREE. Although it is true that the data summarized in Mallet 2005 was indeed based largely on morphologically identified species (and their hybrids), it doesn’t rely on a morphological species concept. Anyone who knows taxonomy of any group of organisms knows also that morphology is a rather good, although not foolproof, guide to species status; two sister species, when they co-occur in sympatry, will typically display two modes in multivariate morphospace. Actually, Mallet in 1995 and 2005 argues for a genotypic cluster definition of species, which certainly applies to molecular markers as well as morphology. Two related species, if they co-occur in sympatry, will display a series of genetic differences that enables them to be identified, even if they hybridize. There are two modes in the multivariate genotypic distribution; the relationship with the classical taxonomist’s morphological identification of species is clear.

Then you argue “the emergence of molecular data ... enables substituting the human-made species concept with genetic clusters that quantitatively vary in their level of genetic distance (18),” where ref. 18 is Galtier 2019 in Evolutionary Applications. Now that is interesting, as I think Galtier proposes “Species are defined as entities sufficiently diverged such that gene flow (arrows) is very rare or inexistent” (his Fig. 1). In other words, he appears to have a species concept such that gene flow between species is zero. Any gene flow, he argues, would render the situation “ambiguous”.

Later, perhaps recognizing that this is too extreme, Galtier proposes using a reference species based system: “...to identify taxa in which large amounts of data are available, and species boundaries are consensual, or can be agreed on. Species delineation in any other taxon could thus be achieved so as to maximize consistency with the reference [taxa].”

Now perhaps this dickering about what is a species appears rather unreasonable, since I think we all know (and Nicolas Galtier certainly seems to agree) that there is a continuum between populations that are not species and those that are species. However, in order to disprove the prevailing narrative that plant species hybridize more than animal species, you really must take a stance on what you mean by a species, and what you mean by a population that is not a species. My natural history knowledge of flowering plants and animals such as insects and birds suggests that plant species that co-occur in sympatry really do have a higher rate of hybridization than animal species. Not only is a greater fraction of species involved, but when they do hybridize, there are usually a lot more hybrids.

But you will say perhaps: “that is not really the question we attempt to answer.” And indeed it is not, so perhaps you should not have complained that that finding about whether species hybridize was an artefact, which you appear to do.

The question you more attempt, I think, to answer is: “is introgression more common in plants than in animals for a given level of genetic divergence, DA?” Rather than a question about species, it seems to me you are asking a question here that is independent of what your (or the reader’s species) concept is (unless you argue that a species has a certain threshold level of genetic divergence).

After arguing that “the Tree of Life” is “interrupted by species barriers that are progressively established in their genome as the divergence between evolutionary lineages increases,” you then argue that “The consequences of reproductive isolation can therefore be captured through the long-term effect of barriers on reducing introgressing introgression locally in the genomes, which provides a useful quantitative metric applicable to any organism (4).”

Ref. 4 is Westram et al. (2022) J. Evol. Biol. “What is reproductive isolation?” Westram show that it’s actually very hard to measure overall reproductive isolation, RI, which they say is determined by the level of “effective migration” at neutral loci, or the fraction of the rate of neutral genes that actually establish (reduced due to species barriers) in the recipient population, me, divided by the rate of “potential gene flow,” m, into the population caused by the potential for hybridization and backcrossing, or RI = 1 - me/m. Effective gene flow depends on where in the genome you measure it; in which direction you measure gene flow; whether populations are parapatric or sympatric; whether you want to measure it using an “organismal” or “genetic” focus (in Westram et al.’s terminology). Furthermore, it depends on who is measuring it and how. Everyone who measures it seems to have somewhat different measures of reproductive isolation (Sobel, J. M., & Chen, G. F. (2014). Unification of methods for estimating the strength of reproductive isolation. Evolution, 68, 1511–1522). It doesn’t provide a very useful comparative measure applicable at the whole species level at all. My colleague from Boston University and I conclude from perusing the lengthy discussions in Sobel & Chen and Westram et al. that measuring overall reproductive isolation is unlikely to be useful, and we would be better off just accepting that it is a vague heuristic which expresses something about species (Mallet, J., & Mullen, S.P. 2022. J. Evol. Biol. 35:1175-1182). In contrast, one can readily measure some of its many components, such as “hybrid inviability”, “assortative mating” and so on, and these remain useful and interesting at the whole species level and as comparative indicators.

Again, it may seem a distraction that I am discussing what is reproductive isolation, but it seems important here, because you are using a measure of reproductive isolation, and then relating it to genetic distance. In Westram et al., the main concern was to develop an experimental measure of reproductive isolation. Westram et al cautioned against estimating reproductive isolation from sequence data, which is the method you employ here. Their reasoning is that sequence divergence is a consequence only of actual gene flow, me (after taking into account barriers to gene flow), and that there is no way of estimating “potential gene flow” from the same data. In the main part of the paper (e.g. the data points in Fig. 1A), there seems to be a non-continuous measure of reproductive isolation, such that “migration” has a value 1, whereas “isolation” has a value zero. It was not entirely clear to me why this should be so, since, whatever it is, it seems clear to me that reproductive isolation should surely be a continuous parameter. Delving into the supplement, I found that “genetic isolation” was indicated “when our ABC framework yields a posterior probability P(migration) < 0.1304. This threshold was empirically determined by the robustness test conducted in (Ref. 6).” Similarly, the same robustness test yielded “strong statistical support for ongoing migration ... when the posterior probability P(migration) > 0.6419.” Pairs of taxa with intermediate posterior probabilities were considered “ambiguous” and were discarded. Note that P(migration) is not the actual mixing rate of the populations, me, or the fraction of the genome exchanged, but, if I understand it correctly, the posterior probability that any gene flow at all occurs. This is a very different measure of reproductive isolation from that proposed by Sobel et al. or Westram et al., or anyone else.

I think the reason for your choice of a measure of reproductive isolation is indicated by the second question you ask in the introduction: “At what level of molecular divergence do species become fully isolated?” This is related to a common conception of species as irreversibly independent lineages, and the idea that speciation will be “complete” when gene flow becomes zero. But in fact, the “completion” of speciation in this sense seems rather unlikely. The progressive loss of compatibility between diverging lineages seems likely to follow some sort of continuous probabilistic failure law, similar to the way lightbulbs fail over time. The simplest failure law is log-linear with time, although more complex models such as the accelerating “snowball” model of hybrid incompatibility, or the likely “slowdown” model for selective reinforcement, are also possible (Gourbière, S., & Mallet, J. 2010. Are species real? The shape of the species boundary with exponential failure, reinforcement, and the "missing snowball". Evolution 64:1-24); but all have a long asymptotic tail. You seem to recognize this stretched out right-hand side timescale by plotting genetic divergence on a log scale in Fig. 1 (although why is “net divergence,” Nei’s DA, the correct scale on which to base such an analysis? You do not explain or justify this). Nonetheless, by making an argument for complete isolation as an endpoint, you ignore the asymptotic nature of compatibility decline to zero. Based on the data we analyzed, it is rather hard to estimate the shape of the failure curve, mainly because the accumulation of incompatibilities is so variable, even among closely related species, such as Drosophila fruit-flies, for example. This variability between pairs of species shows up only in the data, and not in the fitted curve in Fig. 1A, but is more evident from Fig. 1B.

Overall, I remain somewhat unconvinced that plants have a more rapid accumulation of species barriers than animals. I agree it is likely that many plants have “less efficient dispersal modalities” than most mobile animals, and that this might mean that actual gene flow becomes lower for plants at a distance from one another, but this is a little different from what I think one would mean by “species barriers.” Reproductive isolation and species barriers should generally be rather independent of geography; in other words reproductive isolation at close range is what we are primarily interested in. This is the problem of using a measure of reproductive isolation that depends purely on actual gene flow. I therefore remain unconvinced that my natural history observations of many plant hybrids in nature, and very few animal hybrids, are not reliable indicators of lower levels of reproductive isolation among plants than among animal species.

On 2022-05-04 17:50:27, user Karel Morawetz wrote:

The manuscript; Human anelloviruses produced by recombinant expression of synthetic genomes is based on two published papers from Johanna Galmès et al., 2013: Potential implication of new torque teno mini viruses in parapneumonic empyema in children (in HEK293T and A549 cell lines) and Yao-Wei Huang et al, 2012: Rescue of a Porcine Anellovirus (Torque Teno Sus Virus 2) from Cloned Genomic DNA in Pigs. (in PK-15 cell line with monomeric or tandem circular genomic DNA of TTSuV2). These papers were published ten years ago, it appears to me there is not so much scientific progress in the Anellovirus field. Unfortunately, the authors did not show that the Molt-4 cell line is able to generate several viral passages and that these viral passages are relatively stable and there is a lower rate of recombination or mutation in the tandem circular genomic DNA of TTMV-LY2 or nrVL4619 after four viral passages at least. Indeed, I do not see any retinal pigment epithelium (RPE) cell assays or other cell line assays with the infection/transduction of the viral particles from Molt-4 or transfection of the circular viral DNA of nrVL4619 with the nLuc reporter (cloned into downstream region of ORF3) before animal study or in the animal study. <br /> I think there is no robust expression of infectious viral particles in Molt-4 cell line. Specially, when I look at the pics. 7-C, it looks like to me there are two types of viral complexes: two 12 x pentamer = 60-mer viral particles and about eight hundred 2 x pentamer = 10-mer small particles. It appears to me that the 10-mer particles (2 x pentamer) run together with 60-mer particles (12 x pentamer) and these 10-mer particles (2 x pentamer) form a kind of 10-mer x 6 = 60 non-capsid agglomerates which harbor/bind viral DNA and protect the viral DNA against DNAse qPCR assay. (vis. Subir Sarke et al.: Structural insights into the assembly and regulation of distinct viral capsid complexes). In addition, I do not see any separation of 5 MDa (12x5) from 1MDa (2x5) particles after iodixanol linear gradient and SEC purification in Fig 7-B. I would guess that the physical DNA titer comes mostly from 2 x pentamer = 10-mer non-capsid small DNA particles. It seems to me there is still not enough circular viral DNA to assembly 12x5 real viral capsid particles in Molt-4 cell line or viral capsid particles (12x5) are unstable and need an assembly-activating protein or ORF1 capsid protein still evolves to form a stable capsid……..

Karel Morawetz

On 2018-12-14 17:27:14, user joebabbs wrote:

From Line 316 in the paper: "No adjustment for multiple comparisons was carried out."<br /> Isn't some kind of correction required for 850K CpGs assayed?

On 2024-04-04 17:09:33, user Steve Gwynne wrote:

Pretty much sums up the Human Overshoot Conundrum with the added need of a cultural revolution.

I've been working on the cultural dimension for some time now and I have reached the conclusion that what is needed is a transition from the growth imperative to the balance imperative.

This accords with the panarchy cycle in terms of shifting from the growth stage to the conservation phase.

https://passel2.unl.edu/vie...%20defines-,panarchy,scales%20of%20space%20and%20time%E2%80%9D "https://passel2.unl.edu/view/lesson/2e6e3c012632/2#:~:text=2014)%20defines-,panarchy,scales%20of%20space%20and%20time%E2%80%9D").

It accords with the necessary transition from a r-selected strategy to a k-selected strategy. It accords with the maximum power principle in that the goal of evolutionary system design is to optimise the balance between the rate of energy transfer with efficiency of energy transfer which means optimising the balance between force functions, resilience functions, adaptability functions and reproductive functions. In other words, maximising survival potential.

https://www.ecologycenter.u...

Finally the transition from the growth imperative to the balance imperative accords with the need for the human species to balance with Earth systems and in particular balance human activity with the natural carbon, oxygen, nitrogen, phosphorus and water cycles to ensure healthy and resilient functioning of these cycles.

It is of course, natural cycle disequilibrium that typifies human ecological overshoot with the exponential growth of high entropy waste associated with an exponentially growing human abiotic environment which cannot be assimilated naturally by nonhuman biotic and abiotic systems.

Therefore I propose that the Post Growth cultural revolution be predicated on the balance imperative with the understanding that nonhuman associated ecological growth needs to be balanced with the human biotic and abiotic enterprise. And that this is a zero sum game between the k-selected strategy and the current r-selected strategy.

I think the meme of 'Post Growth' is more relevant than the meme of Degrowth although degrowth can be seen as sub category of Post Growth. I think Post Growth is more relevant because it better describes what is actually occurring within the panarchy cycle and is therefore more relatable in terms of public education and public discourse in terms of explaining actually existing dynamics regarding human societies hitting per capita limits to economic abiotic growth and human societies hitting per capita ecological carrying capacity limits.

I would suggest limits to economic growth is indelibly linked to breaching carrying capacity limits but further research is needed to qualify that. This hypothesis suggests that capitalism is responsive to both ecological scarcity and ecological carrying capacity breaches through the price mechanism and should be considered as part of the suite of educational tools to inform the public exactly what is going on beyond the false growth narrative being disseminated by politicians, think tanks, the media and business leaders.

Similarly, the capitalist state system does have resilience mechanisms by which economic contraction can be absorbed to some degree. I feel we need to utilise these systems rather than throw the baby out with the bath water.

By educating the public at the same time as leaning on the resilience functions embedded within the state capitalist system, we can help coordinate temporary and long lasting solutions to permanent per capita economic contraction by rerouting energy and material throughput as necessary. Therefore rather than a solely bottom up approach, I think we also need to utilise current top down systems to facilitate bottom up participatory approaches in order to try and create a win win mutualist strategy. This would include allowing maladaptive state capitalist functions to perish.

Thus rather than using post growth dynamics to reject the state capitalist system which I think will make our shared future even more daunting, I suggest we use the state capitalist system to provide ourselves with buffers to deliberate on the next steps.

This would include devising remedial solutions as different parts of the state capitalist system collapses. This means a more gradualist contraction strategy whereby we rationally respond to the changes that are being indicated by the state capitalist system which as I argued above is probably in sync with ecological scarcity and carrying capacity limits via the invisible hand of the market.

This isn't to say that part of the cultural revolution from the growth imperative to the balance imperative is to try and make capitalism more sustainable. It is to recognise that capitalism itself emerged as a bottom up strategy from its mercantile roots and that we can now activate the emergence of another bottom up system from the roots of the capitalist system.

BalancenotGrowth

OnePlanetLiving

On 2024-01-16 06:23:59, user Amit wrote:

This is published - https://www.sciencedirect.c...

On 2024-12-18 00:44:40, user Lydia Bilinsky wrote:

I’d love to get feedback on whether SFq(D) is invariant with regard to conditions in irradiated cell culture.

On 2019-07-07 17:04:45, user Jiarui wrote:

Nice work! Thank you for the tremendous efforts of comparing all these methods! However, I think that different algorithms accept different inputs. For example, scvis uses principal components instead of raw-counts as inputs, otherwise, the error models and the outputs do not make any sense. Typical t-SNE implementations also either explicitly or implicitly do PCA first, and use the top PCs, e.g., 30 PCs as inputs.

On 2023-04-05 15:39:35, user UTK Micro Immunology JC wrote:

Summary. <br /> Murine cytomegalovirus (MCMV) is a widely used animal model for understanding the pathogenesis of its’ human counterpart, Human cytomegalovirus (HCMV). To initiate a productive infection the virus must first gain access to a host cell. MCMV has various glycoproteins on its surface that interact with specific host cellular receptors depending on cell type. It was recently shown that Neuropilin-1 (Nrp1) is important for MCMV entry into a variety of cell types. Depending on the cell type MCMV utilizes different viral glycoproteins to attach and enter host cells. In fibroblasts, viral entry favors the utilization of viral glycoproteins gB in conjunction with gH/gL/gO known as the trimer. In endothelial, epithelial or myeloid cells, viral entry occurs through the use of gB, the trimer and another complex made up of gH/gL/gO/Mck2 which is known as the pentamer. Mck2 or mouse chemokine 2, has dual functionality in both viral entry and chemokine function. Currently it has not been elucidated the host cellular receptor that Mck2 utilizes for entry into host cells. Using a CRISPR/Cas9 screen, this study identifies the MHC-I molecule is implicated in MCK2 dependent entry into macrophages.

Positive feedback. <br /> I felt that the way the paper is organized was logical and easy to follow. The color coding of the different viruses helped to follow along in the graphs. In the in vivo experiments, utilizing both plaque assays and fluorescence levels to confirm results made them more convincing. The restoration of the phenotype by complementation of B2m and CD81 made the results more convincing. Utilizing the two different viruses that either have or lack MCK2 definitely strengthens their argument. In examining the B2m relationship with Mck2, performing the experiments both in primary cells and immortalized cells strengthens the argument. Using different virus strains that have different genetic manipulations of MCK2, is beneficial for showing that the phenotype is due to a defective protein and not just that specific mutation of the protein in that virus strain.

Major Concerns<br /> Given that most of the initial experiments are done in cell culture, I would have expected there to be more replicates. Also why there are different numbers of replicates used between the different virus groups? <br /> Characterizing stromal cells as anything not Cd11c positive is a reach.<br /> The lack of substantial infectivity of these viruses, regardless of the presence of MCK2, in most of these cell lines makes the data hard to believe <br /> I wonder if the current in vivo data can truly tell if lack of H-2 molecules impacts dissemination. Alternatively, it could impact the rate of virus growth in the SG or in other tissues. To truly understand whether dissemination is impacted one must use barcoded viruses.

Minor concerns

While infectivity using these reporter viruses has been assessed by flow cytometry previously, I think that performing a plaque assay would further validate results.

List the actual p values instead of using the star annotation

Minor spelling errors (pg. 25 the strain C57BL/6 is spelled incorrectly)

For Figure 4 C-E, it would be helpful to make the scales on each of the graphs the same to be able to compare between all three graphs.

For Figure 5D, it would be beneficial to show the isotype control in the same panel as the MHC-1 to confirm increase/decrease of expression

For those not in the field, I felt that there was not enough emphasis on what type of cellular entry MCK2 functions in, which would help the reader get a more complete understanding of the results.

For figure 7, it would be more convincing that the viruses lacking MCK2 are in stromal cells if there was a specific marker used for stromal cells<br /> For figure 3C, it is a little unclear what the middle column is demonstrating if it is either a locus or reference sequence. This could be easily clarified in the figure legend or materials/methods section. <br /> In page 5 of the results, when talking about the defective MCK2 and how it was repaired, it would be helpful to make it more clear to the reader for how it was defective and how it was repaired. <br /> Why was the viral load in SG measured at day 7? What if a later time point (e.g., day 14) viral load is the same for two types of the viruses? This needs to be checked.<br /> Which specific H-2 molecules (L,D,K) are important for infection? This could be an interesting point of discussion.<br /> b2M-deficient mice may have weird NK cell response that could play a role in control of MCMV. Can the authors confirm that NK cells were not involved in viral control in these mice?<br /> In experiments even with MOI=1 infection rate is very low, <20%. Why? Would waiting for longer time to detect infected cells allow detecting all cells as infected?

On 2025-07-18 12:54:57, user Bram Bloemen wrote:

Very interesting paper!

I'm wondering whether other DNA extraction protocols might improve your viability inference, as other protocols might better retain original DNA fragment sizes (which are likely lower for extracellular DNA).

For example, we usually use enzymatic lysis and magnetic bead purification for ONT sequencing, since it seems to better protect DNA integrity: https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-023-09537-5 .

We generally see larger reads for freshly extracted isolates than for stored metagenomes, and we see large differences in read sizes between strains in microbiome samples. We think this could be related to how easily different species are lysed throughout the protocol, but we didn't test this yet.

In our hands, bead-beating and spin columns caused read lengths to be lower and to have a more homogeneous size distribution.

On 2017-08-22 03:29:15, user Camilo Libedinsky wrote:

In line 790: "perhaps there is also a computational benefit to the balance of mixed and pure selectivity found in the data. Particularly, in order to read out the task variable identity inputs themselves, pure selectivity may be of more use. Retaining pure selectivity could be a tool then for staying flexible." Why would you think that retaining pure selectivity could be a tool then for staying flexible? Wouldn't that be a better description for mixed selective cells?

On 2020-03-29 00:29:13, user Andrew Schaumberg wrote:

Please an extended abstract of this work published as Schaumberg et al 2020 "Machine learning for real-time search and prediction of disease state to aid pathologist collaboration on social media" at the Pathology Visions 2019 conference of the Digital Pahtology Association https://www.ncbi.nlm.nih.go...<br /> I would humbly add that indeed, authors WC and SJC made equal conributions.

On 2018-03-05 23:52:13, user Chris Gorgolewski wrote:

Cross posted from: http://academickarma.org/re...

Significance<br /> The paper "Neural responses to naturalistic clips of behaving animals in two different task contexts" describes a new benchmark dataset for brain decoding. It brings a breath of fresh, unique quality in the context of similar currently available datasets. It will by no doubt be recognized as a valuable resource for the years to come. Nonetheless, a few improvements would make the manuscript better.

Comments to author<br /> Mayor:

• Please provide stimuli files in the /stimuli folder linking them to the individual events via the stim_file column in _events.tsv files. See the BIDS specification for details. This is probably the most important improvement to the dataset I came across.

Minor:

• Consider distributing preprocessed version of the datasets. This would allow scientists to run analyses using this dataset without the need to perform preprocessing themselves. In my experience providing a preprocessed version of the data increases its reuse potential. You can just run FMRIPREP on directly OpenNeuro (I recommend using the "--use-syn-sdc" option since the dataset does not include fieldmaps), and it will be available alongside your dataset. The manuscript should include information about the availability of this data and a brief description of FMRIPREP outputs (it's redundant, but convenient for the reader).

• Providing a figure with example frames from each category of stimuli would greatly help readers in understanding the paradigm.

• Similarly plotting the distributions of selected QC parameters would also improve the manuscript.

• The manuscript would benefit from division into sections such as Introduction, Methods, Results, Discussion (where a comparison to other publicly available datasets could be added) and Conclusion.

• It might be useful to consider making it explicit in the title that this paper is a data descriptor.

On 2019-10-02 08:56:43, user Simon Dellicour wrote:

All the related data and scripts are available at https://github.com/sdellico...

On 2020-07-04 04:18:30, user Dialog2Debate wrote:

If that is so, then why don't we find a lot more Asians and fewer Europeans with severe COVID? How does this square with the disease risk factors for COVID of diabetes, obesity and age?

On 2025-06-22 16:20:13, user Lucian Parvulescu wrote:

Congratulations on this excellent preprint — it's an important and timely contribution to crayfish systematics, and I look forward to seeing it fully accepted and published.

Regarding the newly described Astacidae species, I would like to kindly mention that two additional new species were recently published from North America ( https://doi.org/10.11646/zootaxa.5632.3.4) "https://doi.org/10.11646/zootaxa.5632.3.4)") , adding to the one cited in your manuscript from Europe.

Also, the World of Crayfish® initiative ( https://doi.org/10.7717/peerj.18229) "https://doi.org/10.7717/peerj.18229)") is striving to remain up to date with species distributions by promptly indexing new records and even providing type locality references. A brief mention of such global platforms could enhance the visibility of biogeographic data and support broader dissemination within the crayfish research community.

Well done again on this valuable work!

On 2019-07-11 16:35:32, user Carolyn King wrote:

supplemental figures?

On 2022-08-15 09:10:34, user Iratxe Puebla wrote:

Review coordinated via ASAPbio’s crowd preprint review

This review reflects comments and contributions by Luciana Gallo, Lauren Gonzalez, Claudia Molina, Arthur Molines, Srimeenakshi Sankaranarayanan and Sanjeev Sharma. Review synthesized by Iratxe Puebla.

The manuscript studies the role of the long-coding RNA lncRNA H19 in cellular senescence. The results show that H19 levels decline as cells undergo senescence and repression of H19 is triggered by the loss of CTCF and prolonged activation of p53. The loss of H19 leads to increased let7b-mediated targeting of EZH2. The mTOR inhibitor rapamycin maintains lncRNA H19 levels throughout the cellular lifespan preventing reduction of EZH2 and cellular senescence.

The reviewers found the methodology appropriate but raised some comments and suggestions about the paper as outlined below:

Introduction ‘H19 is a highly conserved, maternally expressed imprinted gene and encodes a 2.3 kb long non-coding RNA (lncRNA). It is located immediately downstream of the neighboring gene IGF2.’ - An additional reference to the expression pattern/levels of lncRNA H19 across 'normal' tissues/developmental stages would be useful to provide immediate insight into the contexts where H19 is important and note the conditions where its levels are altered.

‘To characterize the role of H19 in the cellular senescence of somatic cells, we examined H19 expression during replicative senescence of human cardiac fibroblasts’ - The data on changes in expression of H19 with age/culture time is very interesting. Suggest providing some comments on the choice of experimental systems for each experiment and why HCF cells were used to study replicative senescence while other experiments were completed in skin samples.

Figure 1

Figure 1a - Please indicate in the legend how far apart or what are the passage numbers for 'early' and 'late' passages for the cell culture experiments. Is the reduction in H19 gradual or does it sharply decrease after a certain number of passages? What biological meaning would either of these observations have and how does it relate to mouse data in vivo?

Supplementary Figure 1 shows a sharp drop between PD 20 and PD 50. Would it be possible to provide a finer analysis of H19 levels across many cell passages?

Figure 1b - Recommend using the same normalization in a) and b). In a) levels are normalized to the first condition "early" while in b) levels are normalized to the second condition "old".

Figures 1d and g - Please provide further information on how Cumulative population doublings were measured and clarification for the numbers on the Y axis.

‘decreased the lifespan of cells (Figure 1d; Figure 1-figure supplement 1c)’ - Figure 1d measures cells' doubling time, not lifespan. If lifespan is being inferred from doubling time, please provide some clarification on how this is being done. There are fewer cells after 15 days but it does not mean that cells are dying, it could be that they are growing slower. Please also provide details for the methodology followed to obtain the data in this panel.

Figure 2

‘CTCF mRNA and protein levels decreased in the late passage cells (Figure 2a and b), and CTCF knockdown in early passage cells induced premature senescence characterized by increased SA-?-gal staining and reduction in proliferation (Figure 2-figure supplement 2a). In contrast, treatment with rapamycin mitigated CTCF depletion, which is consistent with the effect of rapamycin maintaining H19 levels (Figure 2a and b). Furthermore, the regulatory link between CTCF and H19 is supported by decreased H19 expression in CTCF-targeted cells (Figure 2c).’ - CTCF knockdown and rapamycin treatment can affect many pathways, recommend toning down this conclusion. In Supplemental Figure 2a, the % of positive cells in the siNeg condition is significantly higher than in Figure 1e (close to 50% in Sup Fig 2a vs 30 % in Fig 1e). Recommend providing some comments on the variability of the control value as that level of variability can confound the conclusions. For example, the siCTCF condition is lower than the siNeg control condition when compared with the value from Sup Fig 2a but not when compared with the value from Fig 1e.

Figure 2d - Remove "presentation last saved just now" from the panel.

‘a stress-dependent downregulation of CTCF through proteasomal degradation of CTCF protein in endothelial cells (51)’ - The paper cited here discusses epithelial cells, should the reference to endothelial cells be updated?

Figure 3 - Please provide further clarification regarding acute stress or prolonged activation of p53. What are the timescales? How do these relate to replicative senescence seen with aging or as cells at late passages?

‘Together these results confirm that activation of p53 is responsible for the downregulation of H19 as part of DNA damage response’ - Please provide further clarification regarding the reference to DNA damage. Is this an inference from the statement about "activation of p53 is crucial for establishing senescence as part of DDR"? p53, like CTCF and mTOR, can play different roles.

‘Given the mounting evidence suggesting the role of lncRNA H19 as a competing endogenous RNA (ceRNA) or miRNA sponge (60–62), we speculated that H19 might mediate the senescence program by regulating miRNA availability. To determine which miRNAs are directly regulated by lncRNA H19 during senescence, we evaluated miRNA expression profiles in control and H19 targeted cells (Figure 4a).’ - Can some further clarification be provided for this claim, if H19 is acting as a miRNA sponge, it wouldn't affect its overall levels, but rather its ability to bind its target genest? Based on the data presented, the link between let7b and H19 appears to be more related to let7b expression than sequestration. Consider removing the fragment or revising it to clarify the mechanistic link drawn between H19 and let7b. To show that H19 is acting as a sponge in this system, it may be necessary to mutate the complementary sequence and check whether let7b's activity increases (i.e. its target genes are down-regulated).

‘Among the top miRNAs upregulated in H19 depleted cells were members of the let7 family; specifically, let7b expression was significantly upregulated (Figure 4b’ - Suggest adding some more information about the other miRNAs that are affected.

Figure 4f ‘Senescence-associated secretory’ - Please clarify why SERPINE mRNA level is considered instead of IL-6 as in Figure 1f.

‘suggests the loss of EH2 results in a general decrease in PRC2 activity’ - should EH2 read EZH2?

Figure 5 - What happens to CDKN2A levels when H19 is depleted or overexpressed? Can the H3Kme3 antibody binding data be supported with expression data for CDKN2A? It may be relevant to see whether it follows the expectation that loss of H19 reduces EZH2 expression and increases p16 expression.

Figure 6 - Please provide some brief clarification for what the solid and dashed lines represent in the model.

‘More importantly, prolonged treatment with mTOR inhibitor rapamycin maintains lncRNA H19 levels by preventing the loss of CTCF expression and activation of p53, thus preventing the induction of senescence.’ - There is a question as to whether the experiments presented support this statement, suggest reframing the fragment. The strongest mechanistic experiments in the study are those regarding let7b, because they use the mimic to "rescue" its function.

Supplementary Figure 1d - It is nice to see authors tested 2 different siRNAs for H19 and these showed the same effect in Panel d. Can some discussion be provided for why overexpression of H19 leads to an increase in senescence markers and reduced proliferation.The outcomes of siRNA experiments may not sufficiently support the correlation between H19 levels and senescence induction. This is an example where both excess H19 and reduced levels of H19 have the same effect and it is a very important result. Would it be possible to titrate the expression of H19 to achieve different levels of overexpression and then analyze senescence markers under these conditions? It may also be possible to generate a siRNA-resistant overexpression construct to rescue the effects seen with siRNA-mediated depletion of H19.

Supplementary Figure 5 - Recommend updating the presentation to more clearly highlight the decrease in binding as mentioned in the main text.

Methods

‘10g of plasmid DNA was transfected’ - should this read 10 micrograms?

‘??CT method’ - Please clarify the control for calculating relative mRNA levels.

‘Cells were incubated with EdU stain (100mM Tris (pH8.5), 1mM CuSO4, 1.25 uM Azide Fluor 488, and 50mM ascorbic acid) at room temperature for 30 mins. Cells were washed with PBS twice and imaged using EVOS FL Auto microscope (Thermo Fisher)’ - Please report the duration that the cells were incubated with EdU in culture before the cells were fixed and EdU incorporated in the DNA was stained.

On 2020-11-24 18:19:23, user Ferrandon wrote:

We would also like to thank Mark Hanson, Steven Wasseman, and Bruno Lemaitre for sharing their data with us and discussions on the Baramicin family. Their work is accessible at: https://www.biorxiv.org/con....<br /> Jianqiong Huang, Samuel Liegeois, and Dominique Ferrandon

On 2016-05-27 17:20:14, user steelnpearls wrote:

I have a very severve traumatic brain injury that after 8 yrs post near falal I am now able to live well. I was told by my Traumatic Brain Injury Specialist to NEVER have a cell phone as it could damage my healing brain. I am now very sensitive to Electro-Magnation Electricity in all it's possible uses. It's very difficult to go out and I shop for groceries at night past 10PM so as not to have many in the store with cell phone in use. My TBI doctors have in my patient record now I am sensitive to Wi-Fo and EFF and have put that into my patient record they keep on me as a lifetime TBI patient with UT Southwestern University in Dallas, TX. All this reserch is true and the facts you are finding is true and plausible. Remember Beau Biden and there was Jimmy Gonzalves in Michigan Please know I call cell phones and Advanced Electric Meters MONSTERS to all living matter on this planet. Thank you My name is Deborah Wiseman.

On 2020-07-17 15:02:31, user Paul Gordon wrote:

Very interesting, thanks for posting. In the text, 305 genomes are described, but in Table S1 there are 222 Austrian genomes. Is this due to duplicate sampling, not listing genomes outside the superclusters, or something else? Thanks for any clarification you can provide!

On 2020-07-02 17:20:22, user Arunava Roy wrote:

I thought CoV-2 ORF3B has a 20 aa truncation compared to CoV and is not expressed (only 22 aa long).

On 2020-08-17 13:30:58, user ricardo wrote:

Hey!, its great to see an article which talk about the issues of open science, bad practices and the misuse of preprints by the media..<br /> Just 2 comments: <br /> Regarding the characterization of the problem in the methodology, do u think could be interesting to add the need to have a defined structure in the methodology that favors reproducibility, for example, using RRIDs, (which will depend on the area and research paradigms)<br /> In the solutions, perhaps also suggest platforms such as Octopus (https://demo.science-octopu...) or hypergraph (https://www.libscie.org/hyp... "https://www.libscie.org/hypergraph)")... as others ways of communicating the research carried out, facilitating suggestions, correct and publish?

On 2023-02-21 13:25:17, user Giorgio Cattoretti wrote:

We read with much interest your evaluation and comparison of dimensionality reduction (DR) algorithms, and we are intrigued by your finding that CYTOF data are somewhat “continuous”, or at least “have a much larger range than those of scRNA-seq and will be pre-processed in various steps, which loses their discrete count nature.”<br /> Including IMC (in situ multiplex) data in your analysis may not be appropriate because in situ antibody-based data are even more broadly spread, because of imperfect cell segmentation (and bleeding from neighbors), partial cell sectioning, specimen thickness, etc. etc.<br /> Because of the continuous nature of in situ data, we devised a data pre-processing step, Lognormal Shrinkage (see our publication BRAQUE, https://www.mdpi.com/1099-4... ), which dramatically helps the clustering and the cell identification steps.<br /> Bayesian Reduction for Amplified Quantization in UMAP Embedding results in a more granular an accurate cell identification, pointing at data pre-processing as a crucial step for continuous type of data.<br /> It would be interesting to analogously pre-process CYTOF data as we did and then compare DR algorithms. By the same token, we made available in the supplementary BRAQUE materials, in situ multiplex data, obtained with the MILAN technology ( https://www.researchsquare.... ), comprising 80 markers and up to more than half a million cells.

Prof. Giorgio Cattoretti

On 2017-12-05 13:37:55, user aged wrote:

The authors aggregate, ad-hoc, a bunch of random transcriptomic data sets and analyze them with only a cursory attention to batch effects or underlying technical differences among the experiments. The authors' in-house RNAi lifespan experiments fail to produce the expected lifespan extensions cited elsewhere in the literature, raising serious questions about the lab procedures used.

One wonders what motivation the employees at Gero LCC might have, to post such a sloppy study.

On 2022-04-14 18:36:40, user Elle Tigre wrote:

Great! Next, check biomarkers of the stool!